Instructions to use Efficient-Large-Model/SANA-WM_bidirectional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Efficient-Large-Model/SANA-WM_bidirectional 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("Efficient-Large-Model/SANA-WM_bidirectional", 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") - Notebooks
- Google Colab
- Kaggle
File size: 168 Bytes
e6e8923 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"cache_implementation": "hybrid",
"do_sample": true,
"eos_token_id": [
1,
106
],
"top_k": 64,
"top_p": 0.95,
"transformers_version": "4.57.3"
}
|