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[Revision] Don't recommend using revision (#1764)
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‎docs/source/api/pipelines/overview.mdx

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@@ -139,9 +139,9 @@ from diffusers import StableDiffusionImg2ImgPipeline
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# load the pipeline
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device = "cuda"
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", revision="fp16", torch_dtype=torch.float16
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).to(device)
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to(
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device
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)
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# let's download an initial image
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url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"
@@ -189,7 +189,6 @@ mask_image = download_image(mask_url).resize((512, 512))
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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"runwayml/stable-diffusion-inpainting",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")

‎docs/source/api/pipelines/stable_diffusion_2.mdx

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@@ -113,7 +113,7 @@ import torch
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# load model and scheduler
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model_id = "stabilityai/stable-diffusion-x4-upscaler"
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pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
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pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipeline = pipeline.to("cuda")
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# let's download an image

‎docs/source/optimization/fp16.mdx

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@@ -79,7 +79,7 @@ To save more GPU memory and get even more speed, you can load and run the model
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```Python
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")
@@ -107,7 +107,7 @@ from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")
@@ -134,7 +134,7 @@ from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")
@@ -159,7 +159,7 @@ from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")
@@ -179,7 +179,7 @@ from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")
@@ -234,7 +234,6 @@ def generate_inputs():
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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).to("cuda")
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unet = pipe.unet
@@ -298,7 +297,6 @@ class UNet2DConditionOutput:
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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).to("cuda")
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@@ -349,7 +347,6 @@ import torch
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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).to("cuda")
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‎docs/source/using-diffusers/custom_pipeline_examples.mdx

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@@ -58,7 +58,6 @@ guided_pipeline = DiffusionPipeline.from_pretrained(
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custom_pipeline="clip_guided_stable_diffusion",
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clip_model=clip_model,
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feature_extractor=feature_extractor,
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revision="fp16",
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torch_dtype=torch.float16,
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)
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guided_pipeline.enable_attention_slicing()
@@ -113,7 +112,6 @@ import torch
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114113
pipe = DiffusionPipeline.from_pretrained(
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"CompVis/stable-diffusion-v1-4",
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revision="fp16",
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torch_dtype=torch.float16,
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safety_checker=None, # Very important for videos...lots of false positives while interpolating
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custom_pipeline="interpolate_stable_diffusion",
@@ -159,7 +157,6 @@ pipe = DiffusionPipeline.from_pretrained(
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"CompVis/stable-diffusion-v1-4",
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custom_pipeline="stable_diffusion_mega",
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torch_dtype=torch.float16,
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revision="fp16",
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)
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pipe.to("cuda")
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pipe.enable_attention_slicing()
@@ -204,7 +201,7 @@ from diffusers import DiffusionPipeline
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import torch
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206203
pipe = DiffusionPipeline.from_pretrained(
207-
"hakurei/waifu-diffusion", custom_pipeline="lpw_stable_diffusion", revision="fp16", torch_dtype=torch.float16
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"hakurei/waifu-diffusion", custom_pipeline="lpw_stable_diffusion", torch_dtype=torch.float16
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)
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pipe = pipe.to("cuda")
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@@ -268,7 +265,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
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custom_pipeline="speech_to_image_diffusion",
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speech_model=model,
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speech_processor=processor,
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revision="fp16",
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torch_dtype=torch.float16,
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)
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‎docs/source/using-diffusers/img2img.mdx

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@@ -24,9 +24,9 @@ from diffusers import StableDiffusionImg2ImgPipeline
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# load the pipeline
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device = "cuda"
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", revision="fp16", torch_dtype=torch.float16
29-
).to(device)
27+
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to(
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device
29+
)
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# let's download an initial image
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url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"

‎docs/source/using-diffusers/inpaint.mdx

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@@ -42,7 +42,6 @@ mask_image = download_image(mask_url).resize((512, 512))
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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"runwayml/stable-diffusion-inpainting",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")

‎examples/community/README.md

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@@ -57,7 +57,7 @@ guided_pipeline = DiffusionPipeline.from_pretrained(
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custom_pipeline="clip_guided_stable_diffusion",
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clip_model=clip_model,
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feature_extractor=feature_extractor,
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revision="fp16",
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torch_dtype=torch.float16,
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)
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guided_pipeline.enable_attention_slicing()
@@ -208,7 +208,7 @@ import torch
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pipe = DiffusionPipeline.from_pretrained(
209209
'hakurei/waifu-diffusion',
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custom_pipeline="lpw_stable_diffusion",
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revision="fp16",
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torch_dtype=torch.float16
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)
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pipe=pipe.to("cuda")
@@ -275,7 +275,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
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custom_pipeline="speech_to_image_diffusion",
276276
speech_model=model,
277277
speech_processor=processor,
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revision="fp16",
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torch_dtype=torch.float16,
280280
)
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@@ -333,7 +333,7 @@ import torch
333333
pipe = DiffusionPipeline.from_pretrained(
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"CompVis/stable-diffusion-v1-4",
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custom_pipeline="wildcard_stable_diffusion",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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prompt = "__animal__ sitting on a __object__ wearing a __clothing__"
@@ -567,7 +567,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
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detection_pipeline=language_detection_pipeline,
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translation_model=trans_model,
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translation_tokenizer=trans_tokenizer,
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revision="fp16",
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torch_dtype=torch.float16,
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)
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@@ -615,7 +615,7 @@ mask_image = PIL.Image.open(mask_path).convert("RGB").resize((512, 512))
615615
pipe = DiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-inpainting",
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custom_pipeline="img2img_inpainting",
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revision="fp16",
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torch_dtype=torch.float16
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)
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pipe = pipe.to("cuda")

‎examples/community/wildcard_stable_diffusion.py

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@@ -68,7 +68,7 @@ class WildcardStableDiffusionPipeline(DiffusionPipeline):
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Example Usage:
6969
pipe = WildcardStableDiffusionPipeline.from_pretrained(
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"CompVis/stable-diffusion-v1-4",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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prompt = "__animal__ sitting on a __object__ wearing a __clothing__"

‎src/diffusers/pipelines/README.md

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@@ -113,7 +113,6 @@ from diffusers import StableDiffusionImg2ImgPipeline
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device = "cuda"
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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revision="fp16",
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torch_dtype=torch.float16,
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).to(device)
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@@ -161,7 +160,6 @@ mask_image = download_image(mask_url).resize((512, 512))
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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"runwayml/stable-diffusion-inpainting",
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revision="fp16",
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torch_dtype=torch.float16,
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)
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pipe = pipe.to("cuda")

‎tests/pipelines/altdiffusion/test_alt_diffusion.py

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@@ -248,9 +248,7 @@ def test_alt_diffusion_fast_ddim(self):
248248
def test_alt_diffusion_text2img_pipeline_fp16(self):
249249
torch.cuda.reset_peak_memory_stats()
250250
model_id = "BAAI/AltDiffusion"
251-
pipe = AltDiffusionPipeline.from_pretrained(
252-
model_id, revision="fp16", torch_dtype=torch.float16, safety_checker=None
253-
)
251+
pipe = AltDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
254252
pipe = pipe.to(torch_device)
255253
pipe.set_progress_bar_config(disable=None)
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