Instructions to use stabilityai/stable-audio-3-optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Stable Audio 3
How to use stabilityai/stable-audio-3-optimized with Stable Audio 3:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Add pre-processed FP16-mixed ONNX for SA3 DiTs
Browse filesShips dit_fp16mixed.onnx alongside the original FP32 dit.onnx for each
SA3 DiT (sm-music, sm-sfx, sa3-m). Consumers compiling for a non-sm_90
architecture can now build the DiT engine with a plain
`build_from_onnx.py sa3-sm-music` (STRONGLY_TYPED, no precision flags
needed) — no onnx-graphsurgeon dependency required.
The pre-processing was done once with build_dit_fp16mixed.py:
- 140 RMSNorm chains wrapped in Cast(FP32)/Cast(FP16) islands
- 40 attention Softmax nodes wrapped
- ~186 RoPE-region nodes (reachable from Cast(to=FP32) feeding Cos/Sin)
- Non-island weights converted to FP16
ONNX size shrinks roughly in half (1.84 GB → 921 MB for sm-music) because
most weights are now FP16.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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