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
"The file inference_video_scripts/inference_sana_wm.py is missing, the startup example cannot run properly. How to start the example correctly?"
#3
by Jz202408 - opened
python inference_video_scripts/inference_sana_wm.py
--image asset/sana_wm/demo_0.png
--prompt asset/sana_wm/demo_0.txt
--action "w-80,jw-40,w-40,lw-60,w-100"
--translation_speed 0.055
--rotation_speed_deg 1.2
--num_frames 321
--output_dir results/demo
"The file inference_video_scripts/inference_sana_wm.py is missing。