Instructions to use SceneWorks/Sana_1600M_1024px_mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SceneWorks/Sana_1600M_1024px_mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Sana_1600M_1024px_mlx SceneWorks/Sana_1600M_1024px_mlx
- Sana
How to use SceneWorks/Sana_1600M_1024px_mlx 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://SceneWorks/Sana_1600M_1024px_mlx") 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
- Local Apps Settings
- LM Studio
Add SANA MLX mirror (verbatim repackage of NVIDIA diffusers checkpoint into SanaPipeline::from_snapshot layout)
eef346e verified | license: other | |
| license_name: nvidia-open-model-license | |
| license_link: LICENSE | |
| library_name: mlx | |
| pipeline_tag: text-to-image | |
| tags: | |
| - sana | |
| - text-to-image | |
| - mlx | |
| - sceneworks | |
| - non-commercial | |
| # SANA 1600M 1024px — SceneWorks MLX mirror | |
| Un-gated, repackaged mirror of [`Efficient-Large-Model/Sana_1600M_1024px_diffusers`](https://huggingface.co/Efficient-Large-Model/Sana_1600M_1024px_diffusers) | |
| for the [SceneWorks](https://github.com/SceneWorks) native MLX worker (`mlx-gen-sana`). | |
| The tensors are **copied verbatim** (dtype-preserving — no conversion, no | |
| re-quantization) into the directory layout that `SanaPipeline::from_snapshot` | |
| expects: | |
| ``` | |
| transformer/diffusion_pytorch_model.safetensors # SANA 1.6B Linear-DiT trunk (F16) | |
| vae/diffusion_pytorch_model.safetensors # 32x DC-AE f32c32 decoder (F32) | |
| text_encoder/gemma-2-2b-it.safetensors # gemma-2-2b-it CHI caption encoder (BF16) | |
| text_encoder/tokenizer.json | |
| ``` | |
| The gemma-2-2b-it text encoder is sourced from the un-gated | |
| [`SceneWorks/gemma-2-2b-it`](https://huggingface.co/SceneWorks/gemma-2-2b-it) | |
| mirror (merged from its two shards into one file) so the SANA snapshot is | |
| self-contained. | |
| ## License — NON-COMMERCIAL | |
| SANA is distributed under the **NVIDIA Open Model License** (see [`LICENSE`](LICENSE) | |
| and [`NOTICE`](NOTICE)). This is a non-commercial license: the model and its | |
| outputs are for **research and evaluation use only**. By downloading these | |
| weights you agree to the NVIDIA Open Model License terms. The bundled gemma-2-2b-it | |
| encoder is under the Google Gemma Terms of Use. | |
| This mirror adds no additional grant and alters no weights. | |