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Update README.md

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@@ -3,6 +3,11 @@ base_model:
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  - stabilityai/stable-diffusion-2-inpainting
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  - stabilityai/stable-diffusion-2-1
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  pipeline_tag: image-to-image
 
 
 
 
 
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  ---
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  # **Example Outputs**
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@@ -66,4 +71,4 @@ with torch.autocast('cuda',dtype=torch.bfloat16):
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  with torch.no_grad():
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  # each model's input image should be one of PIL.Image, List[PIL.Image], preprocessed tensor (B,3,H,W). Image must be 3 channel
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  image_gray_restored = gray_inpaintor(image_gray_masked, num_inference_steps=250, seed=10)[0].convert('L') # you can pass 'mask' arg explictly. mask : Tensor (B,1,512,512)
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- image_restored = gray2rgb(image_gray_restored.convert('RGB'))
 
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  - stabilityai/stable-diffusion-2-inpainting
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  - stabilityai/stable-diffusion-2-1
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  pipeline_tag: image-to-image
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+ library_name: diffusers
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+ tags:
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+ - inpaint
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+ - colorization
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+ - stable-diffusion
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  ---
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  # **Example Outputs**
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  with torch.no_grad():
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  # each model's input image should be one of PIL.Image, List[PIL.Image], preprocessed tensor (B,3,H,W). Image must be 3 channel
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  image_gray_restored = gray_inpaintor(image_gray_masked, num_inference_steps=250, seed=10)[0].convert('L') # you can pass 'mask' arg explictly. mask : Tensor (B,1,512,512)
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+ image_restored = gray2rgb(image_gray_restored.convert('RGB'))