Instructions to use wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers", 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 wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 1.55 MB
-
https://huggingface.co/wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers/resolve/main/assets/vben_vs_sota.png
- Command line
-
hf download hf://wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers/assets/vben_vs_sota.png
-
curl -L -o vben_vs_sota.png https://huggingface.co/wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers/resolve/main/assets/vben_vs_sota.png
1.55 MB

- Xet hash:
- 36f7b1cbc8b21a2faf9993906e033de586776a6d1b396fa391ceab12cbc84f63
- Size of remote file:
- 1.55 MB
- SHA256:
- 9a0e86ca85046d2675f97984b88b6e74df07bba8a62a31ab8a1aef50d4eda44e
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