Instructions to use yichengup/flux.1-fill-dev-OneReward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yichengup/flux.1-fill-dev-OneReward 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("yichengup/flux.1-fill-dev-OneReward", 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
Improve model card: add library_name, citation and sample usage
#3
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
I've opened this PR to enhance the model card for OneReward-ComfyUI. Specifically, I have:
- Added
library_name: diffusersto the metadata to enable better integration and discoverability. - Included a sample usage code snippet from the official GitHub repository (note that this requires the custom pipeline from their source code).
- Added the BibTeX citation from the paper.
Please let me know if you have any questions!
yichengup changed pull request status to merged