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fix welcome.html link issue (#1962)
Co-authored-by: ZhangJianyu <[email protected]>
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README.md

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@@ -19,8 +19,8 @@ Intel® Neural Compressor aims to provide popular model compression techniques s
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as well as Intel extensions such as [Intel Extension for TensorFlow](https://github.com/intel/intel-extension-for-tensorflow) and [Intel Extension for PyTorch](https://github.com/intel/intel-extension-for-pytorch).
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In particular, the tool provides the key features, typical examples, and open collaborations as below:
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* Support a wide range of Intel hardware such as [Intel Gaudi Al Accelerators](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html), [Intel Core Ultra Processors](https://www.intel.com/content/www/us/en/products/details/processors/core-ultra.html), [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon/scalable.html), [Intel Xeon CPU Max Series](https://www.intel.com/content/www/us/en/products/details/processors/xeon/max-series.html), [Intel Data Center GPU Flex Series](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/flex-series.html), and [Intel Data Center GPU Max Series](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/max-series.html) with extensive testing;
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support AMD CPU, ARM CPU, and NVidia GPU through ONNX Runtime with limited testing; support NVidia GPU for some WOQ algorithms like AutoRound and HQQ.
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* Support a wide range of Intel hardware such as [Intel Gaudi Al Accelerators](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html), [Intel Core Ultra Processors](https://www.intel.com/content/www/us/en/products/details/processors/core-ultra.html), [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon/scalable.html), [Intel Xeon CPU Max Series](https://www.intel.com/content/www/us/en/products/details/processors/xeon/max-series.html), [Intel Data Center GPU Flex Series](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/flex-series.html), and [Intel Data Center GPU Max Series](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/max-series.html) with extensive testing;
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support AMD CPU, ARM CPU, and NVidia GPU through ONNX Runtime with limited testing; support NVidia GPU for some WOQ algorithms like AutoRound and HQQ.
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* Validate popular LLMs such as [LLama2](/examples/pytorch/nlp/huggingface_models/language-modeling/quantization/llm), [Falcon](/examples/pytorch/nlp/huggingface_models/language-modeling/quantization/llm), [GPT-J](/examples/pytorch/nlp/huggingface_models/language-modeling/quantization/llm), [Bloom](/examples/pytorch/nlp/huggingface_models/language-modeling/quantization/llm), [OPT](/examples/pytorch/nlp/huggingface_models/language-modeling/quantization/llm), and more than 10,000 broad models such as [Stable Diffusion](/examples/pytorch/nlp/huggingface_models/text-to-image/quantization), [BERT-Large](/examples/pytorch/nlp/huggingface_models/text-classification/quantization/ptq_static/fx), and [ResNet50](/examples/pytorch/image_recognition/torchvision_models/quantization/ptq/cpu/fx) from popular model hubs such as [Hugging Face](https://huggingface.co/), [Torch Vision](https://pytorch.org/vision/stable/index.html), and [ONNX Model Zoo](https://github.com/onnx/models#models), with automatic [accuracy-driven](/docs/source/design.md#workflow) quantization strategies
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pip install torch --index-url https://download.pytorch.org/whl/cpu
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```
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#### Use Docker Image with torch installed for HPU
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https://docs.habana.ai/en/latest/Installation_Guide/Bare_Metal_Fresh_OS.html#bare-metal-fresh-os-single-click
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https://docs.habana.ai/en/latest/Installation_Guide/Bare_Metal_Fresh_OS.html#bare-metal-fresh-os-single-click
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#### Install torch/intel_extension_for_pytorch for Intel GPU
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https://intel.github.io/intel-extension-for-pytorch/index.html#installation
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https://intel.github.io/intel-extension-for-pytorch/index.html#installation
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#### Install torch for other platform
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https://pytorch.org/get-started/locally
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pip install neural-compressor[tf]
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```
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> **Note**:
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> Further installation methods can be found under [Installation Guide](https://github.com/intel/neural-compressor/blob/master/docs/source/installation_guide.md). check out our [FAQ](https://github.com/intel/neural-compressor/blob/master/docs/source/faq.md) for more details.
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> Further installation methods can be found under [Installation Guide](./docs/source/installation_guide.md). check out our [FAQ](./docs/source/faq.md) for more details.
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## Getting Started
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docs/build_docs/build.sh

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done
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# sed -i 's/.\/docs\/source\/_static/./g' ./source/docs/source/Welcome.md ./source/docs/source/user_guide.md
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#sed -i 's/.md/.html/g; s/.\/docs\/source\//.\//g' ./source/docs/source/Welcome.md ./source/docs/source/user_guide.md
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sed -i 's/.\/docs\/source\/_static/./g' ./source/docs/source/Welcome.md
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sed -i 's/.md/.html/g; s/.\/docs\/source\//.\//g' ./source/docs/source/Welcome.md
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#sed -i 's/\/examples\/README.html/https:\/\/github.com\/intel\/neural-compressor\/blob\/master\/examples\/README.md/g' ./source/docs/source/user_guide.md
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#sed -i 's/https\:\/\/intel.github.io\/neural-compressor\/lates.\/api-doc\/apis.html/https\:\/\/intel.github.io\/neural-compressor\/latest\/docs\/source\/api-doc\/apis.html/g' ./source/docs/source/Welcome.md ./source/docs/source/user_guide.md
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sed -i 's/https\:\/\/intel.github.io\/neural-compressor\/lates.\/api-doc\/apis.html/https\:\/\/intel.github.io\/neural-compressor\/latest\/docs\/source\/api-doc\/apis.html/g' ./source/docs/source/Welcome.md
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sed -i 's/\/examples\/pytorch/https:\/\/github.com\/intel\/neural-compressor\/blob\/master\/examples\/pytorch/g' ./source/docs/source/Welcome.md
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sed -i 's/examples\/README.html/https:\/\/github.com\/intel\/neural-compressor\/blob\/master\/examples\/README.md/g' ./source/docs/source/Welcome.md
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