Instructions to use DarthZhu/VideoRLVR-Wan2.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DarthZhu/VideoRLVR-Wan2.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DarthZhu/VideoRLVR-Wan2.2", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Improve model card with paper link and metadata
#1
by nielsr HF Staff - opened
This PR improves the model card by adding metadata (license, library name, and pipeline tag) and linking it to the associated paper Video Models Can Reason with Verifiable Rewards, project page, and code repository.
DarthZhu changed pull request status to merged