Instructions to use Efficient-Large-Model/Sana_1600M_512px_MultiLing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Sana
How to use Efficient-Large-Model/Sana_1600M_512px_MultiLing with Sana:
# Load the model and infer image from text import torch from app.sana_pipeline import SanaPipeline from torchvision.utils import save_image sana = SanaPipeline("configs/sana_config/1024ms/Sana_1600M_img1024.yaml") sana.from_pretrained("hf://Efficient-Large-Model/Sana_1600M_512px_MultiLing") image = sana( prompt='a cyberpunk cat with a neon sign that says "Sana"', height=1024, width=1024, guidance_scale=5.0, pag_guidance_scale=2.0, num_inference_steps=18, ) - Notebooks
- Google Colab
- Kaggle
Commit History
-
Relicense model under Apache-2.0
Verified signature859e083
-
Update LICENSE.txt
Verified signaturebea22d2 -
Update README.md
Verified signature4dc7dfe
-
Update README.md
Verified signaturef03fa64
-
Create config.json
Verified signature0f06746
-
Update README.md
Verified signaturebacf185 -
Upload 8 files
Verified signatured306561 -
Delete assets
Verified signature66e2c95 -
Create assets/
Verified signature8e71a80 -
Create README.md
Verified signatured6e1198 -
Create LICENSE.txt
Verified signature8c79a9d -
Upload files with `sana-upload`.
Verified signatureUpload checkpoints/Sana_1600M_512px_MultiLing.pthfdcf525 -
initial commit
Verified signature1f49118