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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cpu-amx: add dit_medium_bf16_core.bin (bf16 DiT engine)
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cpu-amx: add dit_medium_bf16_flash.so (bf16 DiT engine)
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cpu-amx: add dit_medium_bf16_pin_fp32.npz (bf16 DiT engine)
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cpu-amx: add dit_medium_bf16_core_manifest.txt (bf16 DiT engine)
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cpu-amx: add dit_medium_bf16.so (bf16 DiT engine)
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Delete old fp16mixed names + retired medium dit_bf16.trt (fp16 rename shipped)
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Rename fp16mixed->fp16 DiT/T5Gemma engines+onnx (copies; deletes follow after code merge)
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Remove redundant w8_bf16 engines (int8 weights fold to bf16 at build → identical size/speed to the bf16 baseline)
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Add sm_120 TRT engines (AOT SWA, wide profile) for the quantized tiers
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cpu-amx: add int8 encoders (same_{s,l}_encoder_int8, SmoothQuant+GPTQ) + README row
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cpu-amx README: consistent <model>_<precision> filenames
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cpu-amx: consistent <model>_<precision> filenames (t5gemma_bf16, dit_medium_int8, same_*_encoder_bf16)
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Add sm_90 TRT engines (wide profile) for the quantized tiers
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Add quantized encoder+decoder tier ONNX (fp8 / w8_bf16, padded encoders)
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Add cpu-amx: torch-free C++/AMX engines (T5Gemma bf16, medium DiT int8, SAME-S/L bf16+int8 decoders, SAME-S/L encoders) + weight blobs + README
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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Add fp8 tier for sm-music / sm-sfx DiTs (clean fp8-linear graft on fp16mixed)
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sm_120 sa3-m: add the fp8 medium-DiT tier (176 fp8 GEMM + 96 bf16 fused MHA, 1.43-1.95x vs fp16mixed) (#7)
- sm_120 sa3-m: add the fp8 medium-DiT tier (176 fp8 GEMM + 96 bf16 fused MHA, 1.43-1.95x vs fp16mixed) (af5680d9cca1dfc854e0dc95ea4e60470b33bc0f)f8e0a0f -
sa3-m fp8: calibrated dit_fp8.onnx (real-conditioning activation + per-channel weight scales, @ryanontheinside #47; refs unchanged dit_fp8lin.onnx.data)
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sa3-m fp8: ship calibrated-bakedmin engine (176 fp8 GEMM + 96 bf16 fused MHA + baked fp32 RoPE; calibration by @ryanontheinside #47)
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sm_120 SAME-L: AOT (graph-capturable) engines + tensorRT/README.md (#6)
- sm_120 SAME-L: AOT (graph-capturable) engines + tensorRT/README.md (1d2139821d87b6160099860d29a82d535269a33b)a05f2d4
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Upload onnx/sa3-m/dit_fp8lin.onnx.data with huggingface_hub
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Upload onnx/sa3-m/dit_fp8.onnx with huggingface_hub
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Upload tensorRT/sm_90/sa3-m/dit_fp8.trt with huggingface_hub
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Fix the bf16 medium DiT: bake RoPE's tables into the graph (clipping 3.112% -> 0.014%) (#5)
- Fix the bf16 medium DiT: bake RoPE's tables into the graph (clipping 3.112% -> 0.014%) (59bd967d4635c6e32b0b2a677d56a21984654b9d)6152b1d -
Rebuild medium DiT fp16-mixed engines (sm_90 + new sm_120): attention now fuses, 4.3x faster (#4)
- Rebuild medium DiT fp16-mixed engines (sm_90 + new sm_120): attention now fuses, 4.3x faster (f3263ec28281132dda00915ad3a83920f3b98730) - Complete the sm_120 engine set (mirror sm_90's 15 files) (dcca4a7a8676aa3846ca92ecf7607d572706d685)06debc3 -
Fix medium DiT FP16-mixed ONNX: bound the RoPE island so attention fuses (4.3x faster, cos 1.0000) (#3)
- Fix medium DiT FP16-mixed ONNX: bound the RoPE island so attention fuses (4.3x faster, cos 1.0000) (b4300a99fc3b12b6c59e2d10218399f672087340)fb17708
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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 -
Add bf16 medium DiT TRT engine (sm_90) — FMHA-fused, medium default (#1)
- Add bf16 medium DiT TRT engine (sm_90) — FMHA-fused, medium default (c8cb8ba88ddea67804bcacbbb9265afcbff03b6f) Co-authored-by: CJ Carr <cortexelus@users.noreply.huggingface.co>9a38efb
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tflite: replace naive same-l/enc_w8a8-dyn.tflite with GPTQ (torch-free, real-audio calibrated)
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tflite: replace naive same-l/enc_w8a32.tflite with GPTQ (torch-free, real-audio calibrated)
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tflite: replace naive same-s/enc_w8a8-dyn.tflite with GPTQ (torch-free, real-audio calibrated)
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tflite: replace naive same-s/enc_w8a32.tflite with GPTQ (torch-free, real-audio calibrated)
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tflite: add same-l/enc_w8a8-dyn.tflite (quantized encoder, varlen)
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tflite: add same-l/enc_w8a32.tflite (quantized encoder, varlen)
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tflite: add same-l/enc_w16a32.tflite (quantized encoder, varlen)
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tflite: add same-s/enc_w8a8-dyn.tflite (quantized encoder, varlen)
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tflite: add same-s/enc_w8a32.tflite (quantized encoder, varlen)
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tflite: add same-s/enc_w16a32.tflite (quantized encoder, varlen)
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tflite: add sa3-m/dit_w16a32.tflite (quantized, varlen+varbatch)
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tflite: add sa3-m/dit_w8a32.tflite (quantized, varlen+varbatch)
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tflite: add sa3-m/dit_w8a8-dyn.tflite (quantized, varlen+varbatch)
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tflite: add same-l/dec_w16a32.tflite (quantized, varlen+varbatch)
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tflite: add sa3-sm-sfx/dit_w16a32.tflite (quantized, varlen+varbatch)
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tflite: add sa3-sm-music/dit_w16a32.tflite (quantized, varlen+varbatch)
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tflite: add same-l/dec_w8a32.tflite (quantized, varlen+varbatch)
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