Instructions to use asdasdadadsss/Wan2.1-T2V-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use asdasdadadsss/Wan2.1-T2V-14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("asdasdadadsss/Wan2.1-T2V-14B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download assets/vben_vs_sota.png from asdasdadadsss/Wan2.1-T2V-14B: direct link, hf CLI and curl.
- Browser
- Download file 1.55 MB
-
https://huggingface.co/asdasdadadsss/Wan2.1-T2V-14B/resolve/main/assets/vben_vs_sota.png
- Command line
-
hf download hf://asdasdadadsss/Wan2.1-T2V-14B/assets/vben_vs_sota.png
-
curl -L -o vben_vs_sota.png https://huggingface.co/asdasdadadsss/Wan2.1-T2V-14B/resolve/main/assets/vben_vs_sota.png
1.55 MB

- Xet hash:
- e30918d0e1e08abefb28eecf6606311e55b06621b4fbe992938545e44aa5ea0f
- Size of remote file:
- 1.55 MB
- SHA256:
- 9a0e86ca85046d2675f97984b88b6e74df07bba8a62a31ab8a1aef50d4eda44e
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