Instructions to use Wan-AI/Wan2.2-S2V-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.2-S2V-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/Wan2.2-S2V-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
Download configuration.json from Wan-AI/Wan2.2-S2V-14B: direct link, hf CLI and curl.
- Browser
- Download file 43 Bytes
-
https://huggingface.co/Wan-AI/Wan2.2-S2V-14B/resolve/refs%2Fpr%2F11/configuration.json
- Command line
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hf download hf://Wan-AI/Wan2.2-S2V-14B@refs/pr/11/configuration.json
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curl -L -o configuration.json https://huggingface.co/Wan-AI/Wan2.2-S2V-14B/resolve/refs%2Fpr%2F11/configuration.json
43 Bytes
| {"framework":"Pytorch","task":"any-to-any"} |