Image-to-Image
Diffusers
StableDiffusionInpaintPipeline
stable-diffusion
stable-diffusion-diffusers
text-guided-to-image-inpainting
endpoints-template
Instructions to use redfoo/stable-diffusion-2-inpainting-endpoint-foo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use redfoo/stable-diffusion-2-inpainting-endpoint-foo 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("redfoo/stable-diffusion-2-inpainting-endpoint-foo", 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
- Xet hash:
- ea1e449f36b3dafd3f19eba0c052d283e68f4e30bbcc483f0cf8be2caefb7000
- Size of remote file:
- 681 MB
- SHA256:
- 1f1fce5bf3a7d2f31cddebc1f67ec9b34c1786c5b5804fc9513a4231e8d1bf10
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