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IgnitiveLabs
/
PocketTTS-ONNX

Text-to-Speech
Pocket-TTS
ONNX
English
tts
Model card Files Files and versions
xet
Community

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
PocketTTS-ONNX
586 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 6 commits
Nimesh Herath
Update LICENSE and README to credit Kyutai's CC-BY-4.0 license
7a821c5 5 days ago
  • .gitattributes
    1.52 kB
    initial commit 7 days ago
  • LICENSE
    2.99 kB
    Update LICENSE and README to credit Kyutai's CC-BY-4.0 license 5 days ago
  • README.md
    4.35 kB
    Update LICENSE and README to credit Kyutai's CC-BY-4.0 license 5 days ago
  • bos_before_voice.npy
    4.22 kB
    xet
    Upload folder using huggingface_hub 7 days ago
  • bundle.json
    25.5 kB
    Upload folder using huggingface_hub 7 days ago
  • flow_lm_flow.onnx
    39.1 MB
    xet
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  • flow_lm_flow_int8.onnx
    9.96 MB
    xet
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  • flow_lm_main.onnx
    303 MB
    xet
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  • flow_lm_main_int8.onnx
    76.3 MB
    xet
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  • mimi_decoder.onnx
    41.5 MB
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  • mimi_decoder_int8.onnx
    22.7 MB
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  • mimi_encoder.onnx
    39.8 MB
    xet
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  • mimi_encoder_int8.onnx
    20.8 MB
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  • text_conditioner.onnx
    16.4 MB
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  • text_conditioner_int8.onnx
    16.4 MB
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  • tokenizer.model
    59.3 kB
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