| --- |
| language: |
| - en |
| license: other |
| license_name: stable-audio-community |
| license_link: LICENSE.md |
| pipeline_tag: text-to-audio |
| base_model: stabilityai/stable-audio-3-medium |
| tags: |
| - audio-generation |
| - music |
| - sound-effects |
| - diffusion |
| - gguf |
| - sa3.cpp |
| --- |
| |
| # Stable Audio 3 Medium — GGUF (for sa3.cpp) |
|
|
| GGUF conversions of [stabilityai/stable-audio-3-medium](https://huggingface.co/stabilityai/stable-audio-3-medium) |
| for [**sa3.cpp**](https://github.com/betweentwomidnights/sa3.cpp) — a portable C++/GGML port of |
| Stable Audio 3, no PyTorch in the loop. Runs on CPU, CUDA, Vulkan, or Metal (Apple Silicon). Every component is validated |
| against the PyTorch reference at cosine similarity ~1.0. |
|
|
| ## Files |
|
|
| This is a multi-file model. Grab the **DiT** + **SAME** at your chosen precision and the |
| **conditioner**, plus the shared **encoder + tokenizer** from the |
| [t5gemma-b-b-ul2-GGUF](https://huggingface.co/thepatch/t5gemma-b-b-ul2-GGUF) repo. |
|
|
| | component | file | notes | |
| |---|---|---| |
| | DiT (diffusion transformer) | `stable-audio-3-medium-dit-1.5B-v1.0-{F16,F32}.gguf` | pick one precision | |
| | autoencoder (SAME-L) | `stable-audio-3-medium-same-l-v1.0-{F16,F32}.gguf` | pick one precision | |
| | conditioner | `stable-audio-3-medium-conditioner-v1.0-F32.gguf` | tiny sidecar (prompt padding + seconds_total) | |
| | encoder + tokenizer | → [t5gemma-b-b-ul2-GGUF](https://huggingface.co/thepatch/t5gemma-b-b-ul2-GGUF) | **shared** across all SA3 variants | |
| |
| **F16** is the production path (~3.5s for 12s of audio on an 8GB laptop GPU); **F32** is for CPU |
| validation. The conditioner + encoder + tokenizer stay F32 (small / quality-critical). |
| |
| ## Usage |
| |
| For use with [**sa3.cpp**](https://github.com/betweentwomidnights/sa3.cpp): |
| |
| ```bash |
| # pip install huggingface_hub |
| python tools/download_models.py --variant medium --encoding f16 # fetches this set + the shared encoder |
| |
| # --model resolves the 5 gguf files in ./models by name |
| sa3-generate --model medium --prompt "upbeat funk groove with slap bass" --out song.wav |
| ``` |
| |
| ## Performance |
| |
| Roughly **3s for a 12s clip** at f16 on an 8GB laptop GPU (RTX 5070), and ~6s on an Apple M4 — end to end, |
| including model load. The sliding-window decoder keeps long generations linear (a 2-minute clip is ~9s on |
| the 5070). CPU works but is ~10× slower. Full numbers + the f16 / flash-attention levers: |
| [docs/BENCHMARKS.md](https://github.com/betweentwomidnights/sa3.cpp/blob/main/docs/BENCHMARKS.md). |
| |
| ## License |
| |
| These are format conversions of [stabilityai/stable-audio-3-medium](https://huggingface.co/stabilityai/stable-audio-3-medium), |
| whose weights Stability AI releases under the [Stability AI Community License](https://stability.ai/license): |
| free for organizations under $1M annual revenue, with commercial use, fine-tuning, and derivative works |
| permitted within that threshold (above it, contact Stability AI for an Enterprise License). Outputs are yours. |
| That license carries over to these converted weights. |
| |
| The upstream [stable-audio-3 source code](https://github.com/Stability-AI/stable-audio-3) is released |
| separately under MIT. Pair these with the shared T5Gemma text encoder, which is Google's under the |
| [Gemma Terms of Use](https://ai.google.dev/gemma/terms). |
| |
| ## Relationship to the original |
| |
| **Format conversions** (weights → GGUF) for inference in sa3.cpp — no retraining, no architectural |
| changes. See [sa3.cpp/docs/DISTRIBUTION.md](https://github.com/betweentwomidnights/sa3.cpp/blob/main/docs/DISTRIBUTION.md) |
| for the naming convention and how the pieces fit together. |
| |
