Instructions to use Wan-AI/Wan-Dancer-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan-Dancer-14B 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("Wan-AI/Wan-Dancer-14B", 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:
- 4c5a34075aa0ccaf4e0d5499426cb44347179d5fc54e54b29fc3699a84ab28cc
- Size of remote file:
- 156 kB
- SHA256:
- fce13bddde1b3ef4a2dc186a1013b326ee13532f4d7f2f5b0d98ed6bb8ae9a3d
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