Instructions to use fluently/Fluently-XL-v3-inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fluently/Fluently-XL-v3-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("fluently/Fluently-XL-v3-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
Rename fluently-xl-v3-inpainting.safetensors to FluentlyXL-v3-inpainting.safetensors
7a356b9 verified - Xet hash:
- a42dae6cf23aacfbfa3a6f78d3702054628650cd70a5f7a9c433fa5ffd35efeb
- Size of remote file:
- 6.94 GB
- SHA256:
- 11ba32251f8e7c48c8ae3de0c0bcdc5398a159d6e7aac0abb34aacbc10423d50
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