Instructions to use Wan-AI/Wan2.1-I2V-14B-480P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-I2V-14B-480P 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-I2V-14B-480P", 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") - Inference
- Notebooks
- Google Colab
- Kaggle
Download assets/i2v_res.png from Wan-AI/Wan2.1-I2V-14B-480P: direct link, hf CLI and curl.
- Browser
- Download file 892 kB
-
https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-480P/resolve/main/assets/i2v_res.png
- Command line
-
hf download hf://Wan-AI/Wan2.1-I2V-14B-480P/assets/i2v_res.png
-
curl -L -o i2v_res.png https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-480P/resolve/main/assets/i2v_res.png
892 kB

- Xet hash:
- 8e940fb0e91151fdbb9188aeb7fd58f65a4985acd014a7bdc298e28bf3f9f723
- Size of remote file:
- 892 kB
- SHA256:
- 6823b3206d8d0cb18d3b5b949dec1217f1178109ba11f14e977b67e1f7b8a248
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