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
Commit History
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Add MLX base-model DiT weights for LoRA training (#2)
- Add MLX base-model DiT weights for LoRA training (be6b0350d3677f5981e36fb9c4a1dd2c75307dd9) Co-authored-by: CJ Carr <cortexelus@users.noreply.huggingface.co>08c64b9
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Add MLX weights for SA3 inference
“Cortexelus”Eight FP16/FP32 npz files for pure-MLX Stable Audio 3 inference on Apple Silicon (~8.4 GB total). - dit_sm-music_f16.npz / dit_sm-sfx_f16.npz / dit_medium_f16.npz DiT diffusion transformers (FP16), each with its conditioner baked under a "cond." key prefix. - same_s_encoder_f32.npz / same_s_decoder_f32.npz (FP32) Shared codec for the two small DiTs. - same_l_encoder_f32.npz / same_l_decoder_f32.npz (FP32) Codec paired with the medium DiT. - t5gemma_f16.npz Text encoder (FP16) with SentencePiece tokenizer bytes embedded.2879a89 -
Create MLX/README.md
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