Text-to-Speech
MLX
Supertonic
supertonic-3-mlx
supertonic-3
apple-silicon
tts
speech-synthesis
multilingual
flow-matching
Instructions to use ambassadia/supertonic-3-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ambassadia/supertonic-3-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir supertonic-3-mlx ambassadia/supertonic-3-mlx
- Supertonic
How to use ambassadia/supertonic-3-mlx with Supertonic:
from supertonic import TTS tts = TTS(auto_download=True) style = tts.get_voice_style(voice_name="M1") text = "The train delay was announced at 4:45 PM on Wed, Apr 3, 2024 due to track maintenance." wav, duration = tts.synthesize(text, voice_style=style) tts.save_audio(wav, "output.wav")
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| """Minimal Supertonic 3 MLX usage — 5 lines, no fluff. | |
| Run from anywhere AFTER ``pip install supertonic-3-mlx`` (or from inside | |
| this directory after ``pip install ./``): | |
| python examples/quickstart.py | |
| """ | |
| from supertonic_3_mlx import Pipeline | |
| import soundfile as sf | |
| # When the package has been pip-installed, this auto-downloads from the Hub | |
| # (~ 400 MB) into the standard Hugging Face cache. After the first run, the | |
| # weights are reused from cache and cold start is ~ 11 ms on M4. | |
| pipe = Pipeline.from_pretrained("ambassadia/supertonic-3-mlx") | |
| wav = pipe.generate( | |
| "Hello world from Apple Silicon. Supertonic 3 runs at one hundred times realtime.", | |
| voice="F1", # one of F1..F5, M1..M5 | |
| lang="en", # ISO 639-1 | |
| ) | |
| sf.write("hello.wav", wav, pipe.sample_rate) | |
| print(f"wrote hello.wav — {len(wav) / pipe.sample_rate:.2f}s of audio") | |