Text-to-Speech
Core ML
Supertonic
speech
audio
tts
ane
apple-silicon
flow-matching
diffusion
multilingual
Instructions to use FluidInference/supertonic-3-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Supertonic
How to use FluidInference/supertonic-3-coreml 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
- Xet hash:
- 60d4c505305a72321fbca295b98bdeaf12ef71acd83e2853faf24c0256e172fc
- Size of remote file:
- 388 Bytes
- SHA256:
- dbf54fc98879ee1c9a213452e16d09367f3c34ad489b175bcae7ef5f74f8d121
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.