Instructions to use Efficient-Large-Model/SANA-WM_streaming with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Efficient-Large-Model/SANA-WM_streaming with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Efficient-Large-Model/SANA-WM_streaming", 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
- Xet hash:
- 2b64ed7a4300cd7c2d59362b940efd9d1d7a7b872244727e12d58be7c2e3155f
- Size of remote file:
- 37.8 GB
- SHA256:
- fec0abd4c149b7ea57f3c70870e99b5213209d7ced50773172b91a0e563a8426
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