Instructions to use NARENTLLC/VBVR-Wan2.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NARENTLLC/VBVR-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("NARENTLLC/VBVR-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
- Xet hash:
- 07f3b3450a4c25fa40428e4f3bf24b568a6801d7d63bb20bd20d83b2b4d1bc1c
- Size of remote file:
- 4.55 MB
- SHA256:
- e3909a67b780650b35cf529ac782ad2b6b26e6d1f849d3fbb6a872905f452458
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