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Update README.md

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@@ -18,16 +18,30 @@ library_name: diffusers
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  ## Diffusers
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  ```python
 
 
 
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  from diffusers import AsymmetricAutoencoderKL, StableDiffusionInpaintPipeline
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- pipe = StableDiffusionInpaintPipeline.from_pretrained(
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- "runwayml/stable-diffusion-inpainting"
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- )
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- pipe.vae = AsymmetricAutoencoderKL.from_pretrained(
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- "cross-attention/asymmetric-autoencoder-kl-x-2"
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- )
 
 
 
 
 
 
 
 
 
 
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  image = pipe(prompt=prompt, image=image, mask_image=mask_image).images[0]
 
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  ```
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  ### Visual
 
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  ## Diffusers
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  ```python
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+ from io import BytesIO
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+ from PIL import Image
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+ import requests
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  from diffusers import AsymmetricAutoencoderKL, StableDiffusionInpaintPipeline
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+
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+ def download_image(url: str) -> Image.Image:
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+ response = requests.get(url)
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+ return Image.open(BytesIO(response.content)).convert("RGB")
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+
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+
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+ prompt = "a photo of a person"
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+ img_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/repaint/celeba_hq_256.png"
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+ mask_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/repaint/mask_256.png"
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+
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+ image = download_image(img_url).resize((256, 256))
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+ mask_image = download_image(mask_url).resize((256, 256))
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+
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+ pipe = StableDiffusionInpaintPipeline.from_pretrained("runwayml/stable-diffusion-inpainting")
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+ pipe.vae = AsymmetricAutoencoderKL.from_pretrained("cross-attention/asymmetric-autoencoder-kl-x-2")
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+ pipe.to("cuda")
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  image = pipe(prompt=prompt, image=image, mask_image=mask_image).images[0]
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+ image.save("image.jpeg")
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  ```
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  ### Visual