Instructions to use diffusionbee/fooocus_inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusionbee/fooocus_inpainting 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("diffusionbee/fooocus_inpainting", 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:
- e5a81b36151678ff175dcc8d38d3875c2d911949a50de3ba1fcb6476a0bdb0e4
- Size of remote file:
- 5.14 GB
- SHA256:
- 9a17627f1383890920d87e76f71fc09d2206c01df28138ce09a7226950127532
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