Instructions to use BricksDisplay/Chatterbox-Turbo-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Chatterbox
How to use BricksDisplay/Chatterbox-Turbo-GGUF with Chatterbox:
# pip install chatterbox-tts import torchaudio as ta from chatterbox.tts import ChatterboxTTS model = ChatterboxTTS.from_pretrained(device="cuda") text = "Ezreal and Jinx teamed up with Ahri, Yasuo, and Teemo to take down the enemy's Nexus in an epic late-game pentakill." wav = model.generate(text) ta.save("test-1.wav", wav, model.sr) # If you want to synthesize with a different voice, specify the audio prompt AUDIO_PROMPT_PATH="YOUR_FILE.wav" wav = model.generate(text, audio_prompt_path=AUDIO_PROMPT_PATH) ta.save("test-2.wav", wav, model.sr) - Notebooks
- Google Colab
- Kaggle
Commit History
Yesterday
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Recommended sampling as general.sampling.* + README section
Verified signatureBackbone GGUFs carry the model's recommended sampling as llama.cpp's general.sampling.* keys (codec.cpp scripts/set-backbone-sampling.py); tensors unchanged.59d4ae8
2 days ago
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Model card: Python usage (codec_cpp.TTS)
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README: explain the llama.cpp + codec.cpp split; llama.rn usage
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README: user-facing model card (files, run with codec.cpp tts-cli, license as upstream)
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4 days ago
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Update codec.cpp version note
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Add GGUF files and model card
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initial commit
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