Instructions to use NYCU-MLLab/State-Space-Flow-Matching-for-Shortcut-Generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NYCU-MLLab/State-Space-Flow-Matching-for-Shortcut-Generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NYCU-MLLab/State-Space-Flow-Matching-for-Shortcut-Generation", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
SSFM Model Variants
This repository contains four SSFM student transformer checkpoints for the Sana 1024px pipeline. The repository contains student transformer weights only; the base pipeline is downloaded separately.
Models
| Directory | Variant | Supported steps | Notes |
|---|---|---|---|
SSFM_fixed_2 |
Fixed-step SSFM | 2 | EMA student checkpoint |
SSFM_fixed_4 |
Fixed-step SSFM | 4 | EMA student checkpoint |
SSFM_unified_24 |
Unified SSFM | 2, 4 | EMA student checkpoint |
SSFM_unified_124 |
Unified SSFM | 1, 2, 4 | EMA student checkpoint |
Base model
Use the official Sana Sprint teacher pipeline:
Efficient-Large-Model/Sana_Sprint_0.6B_1024px_teacher_diffusers
The official base model is not duplicated in this repository.
File layout
Each model directory contains:
config.json
diffusion_pytorch_model.safetensors
Use the selected directory as the STUDENT_MODEL_DIR, FIXED2_MODEL_DIR, or
FIXED4_MODEL_DIR path in the SSFM GitHub code.
License and attribution
These checkpoints are derived from the Sana/Sana-Sprint model family. Please follow the upstream model license and terms when using or redistributing the weights:
https://huggingface.co/Efficient-Large-Model/Sana_Sprint_0.6B_1024px_teacher_diffusers
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