Instructions to use IgnitiveLabs/PocketTTS-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use IgnitiveLabs/PocketTTS-ONNX with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("IgnitiveLabs/PocketTTS-ONNX") 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:
- f27bb7e268b5ed860d7fb27f9bdde12c854e15ab13873d8281424f7bf08b0f42
- Size of remote file:
- 41.5 MB
- SHA256:
- 0015e64026a0b22ea5aad84b42a8a252795a3d5683fa28b7357b159d7eef13a0
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