Image-to-Video
Diffusers
Safetensors
English
Chinese
WanVACEPipeline
video generation
video-to-video editing
refernce-to-video
Instructions to use Wan-AI/Wan2.1-VACE-14B-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-VACE-14B-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("Wan-AI/Wan2.1-VACE-14B-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:
- 8e940fb0e91151fdbb9188aeb7fd58f65a4985acd014a7bdc298e28bf3f9f723
- Size of remote file:
- 892 kB
- SHA256:
- 6823b3206d8d0cb18d3b5b949dec1217f1178109ba11f14e977b67e1f7b8a248
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