Image-to-Image
Diffusers
StableDiffusionInpaintPipeline
stable-diffusion
stable-diffusion-diffusers
text-guided-to-image-inpainting
endpoints-template
Instructions to use philschmid/stable-diffusion-2-inpainting-endpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use philschmid/stable-diffusion-2-inpainting-endpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("philschmid/stable-diffusion-2-inpainting-endpoint", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
by SFconvertbot - opened
text_encoder/model.safetensors
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oid sha256:681c555376658c81dc273f2d737a2aeb23ddb6d1d8e5b3a7064636d359a22668
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unet/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:29a698f37775d5904a958c9cebed98184483dfb441729a8e5f98dd5b65df70c8
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size 1731933536
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vae/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c8b011e5a18c53888d51a81aa28223ddec87b450c14dc9650d9c3ebbcd17624e
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size 167335350
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