Instructions to use developerabu/pocket-tts-mnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use developerabu/pocket-tts-mnn with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("developerabu/pocket-tts-mnn") voice_state = tts_model.get_state_for_audio_prompt( "hf://kyutai/tts-voices/alba-mackenna/casual.wav" ) audio = tts_model.generate_audio(voice_state, "Hello world, this is a test.") # Audio is a 1D torch tensor containing PCM data. scipy.io.wavfile.write("output.wav", tts_model.sample_rate, audio.numpy()) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8adae9b68fc0b154f0532390aacf0105f80b36900bb78e2d1795a3be36716390
- Size of remote file:
- 286 kB
- SHA256:
- 88fbb0d31ec26674e97e531a71758cabe4e0e4e5b5a18dafa783021a7f5c9366
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