Instructions to use Video-Reason/VBVR-Wan2.1-diffsynth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Video-Reason/VBVR-Wan2.1-diffsynth 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("Video-Reason/VBVR-Wan2.1-diffsynth", 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:
- f87e9a73e4e228529ced64ac5e8943e046a21e19ac3e7aff5075667146830c4d
- Size of remote file:
- 307 MB
- SHA256:
- b8345fad02f752c6b2f5de4c44f9c73d5bc6e8cf5d26e3224e16be5b064229a1
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