Instructions to use ntc-ai/model-glue-sd15-sana-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Sana
How to use ntc-ai/model-glue-sd15-sana-text 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://ntc-ai/model-glue-sd15-sana-text") 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
| f50d7a3340d8e33d65e6905d6471ee64c2217a0a20f54a67922f96e02ec6a42b LICENSE | |
| 8786e5eaf37799205bbc1f25cdd4cf4d965a9ad208e544e3a53d2656f7ae62a6 README.md | |
| 1a2db74c6c2d940ee15a845a7e60404ffbe32573757672586a18c578db36a10a alternatives/expanded-source.safetensors | |
| fc7f44369cf21791c4f9ad6b74978dd420be41a76330a1fe32b11f440f3bf925 alternatives/linear-uncalibrated.safetensors | |
| aea09893f34769c9b4eef9c30ab9711c935854ec3cf29571aee81cc2367109d7 config.json | |
| 7d352ba100c91c6167a3926275d6cbb9ea784de7912d83919202d1de55e621f4 configs/linear-distill-fixed.json | |
| aea09893f34769c9b4eef9c30ab9711c935854ec3cf29571aee81cc2367109d7 configs/linear_distill.architecture.json | |
| ceca1ec0fcac308fc6a565452f3dc67ce90dcd21e323acefd6df21cc9c1b78b4 configs/source-residual-fullscale-fixed.json | |
| 726250e6d98abe97c35e61b066ac9211c8ef1759504020c0dd11205105d5880c configs/source_cal.architecture.json | |
| 4dc2536374ff7b33c85e7bf21e55977737d4e3cd7d0a6db9189812972dbdf469 configs/validation-confirmation.json | |
| 12de8ae1a69eff31879911c50068af1a2fe77bd5f56dbbf5cf1e6743464eca06 figures/bench-comparison.jpg | |
| d3f12c915d977e11bbffc83b6e1ba94fabe5feafe2a3a35b0ee6c84e34e77654 figures/first-four-test-prompts.jpg | |
| 635da76e075a43329ac4700a2f3a0e5cb71434be04f0828de29fc0a5b69acbcb manifest.json | |
| d3be2492e49f6eb1bc28a406d35108f1055e3dd19e412792442b4c5d9274bb4d model.safetensors | |
| 5416eac9605b2e0af6b5325be168dbd86bdb8a7d5f241f5481dee417e439c349 reports/mask-metrics.json | |
| fabd67b38e5a5e878f63bbb0f6de0278c4bcc459d0603957ce3603417f1fddf2 reports/retraining.json | |
| e57fe58d25d63912d2bbf3bbc814301f760b841c1f49babc648a9d05396910c3 reports/selection.json | |
| 4014fe544e8087ad654a596d7010212b3be99880d609ff22c6ad0fd8d637b36f reports/test-results.json | |