Instructions to use weizhou03/Wan2.1-Fun-1.3B-InP-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use weizhou03/Wan2.1-Fun-1.3B-InP-Diffusers 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("weizhou03/Wan2.1-Fun-1.3B-InP-Diffusers", 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:
- 4c1e09756e427ccda810e8c6cbbbdf55bc660fa672d943538a8fa7b25ddb72f5
- Size of remote file:
- 1.79 MB
- SHA256:
- b0e225caffb4b31295ad150f95ee852e4c3dde4a00ac8f79a2ff500f2ce26b8d
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