Instructions to use Wan-AI/Wan2.1-T2V-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-T2V-1.3B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
Download models_t5_umt5-xxl-enc-bf16.pth from Wan-AI/Wan2.1-T2V-1.3B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 GB
-
https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/resolve/fddfd7ce1aac8af6f8caa0e486bd04ee6c6f29a4/models_t5_umt5-xxl-enc-bf16.pth
- Command line
-
hf download hf://Wan-AI/Wan2.1-T2V-1.3B@fddfd7ce1aac8af6f8caa0e486bd04ee6c6f29a4/models_t5_umt5-xxl-enc-bf16.pth
-
curl -L -o models_t5_umt5-xxl-enc-bf16.pth https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/resolve/fddfd7ce1aac8af6f8caa0e486bd04ee6c6f29a4/models_t5_umt5-xxl-enc-bf16.pth
11.4 GB
- Xet hash:
- 3e714e0465e395272125efc1e40285f98f7db81956d921339db5938e2ec4f6f3
- Size of remote file:
- 11.4 GB
- SHA256:
- 7cace0da2b446bbbbc57d031ab6cf163a3d59b366da94e5afe36745b746fd81d
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