Instructions to use mlx-community/chatterbox-multilingual-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/chatterbox-multilingual-v3 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir chatterbox-multilingual-v3 mlx-community/chatterbox-multilingual-v3
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
mlx-community/chatterbox-multilingual-v3
This is Chatterbox Multilingual V3, converted to MLX format from ResembleAI/chatterbox using mlx-audio version 0.4.7.
Note: This model requires the S3Tokenizer weights from mlx-community/S3TokenizerV2, which will be downloaded automatically.
Use with mlx-audio
pip install -U mlx-audio
Command line
mlx_audio.tts.generate --model mlx-community/chatterbox-multilingual-v3 --text "Bonjour, voici Chatterbox sur MLX !" --ref_audio reference.wav --lang_code fr
Python
from mlx_audio.tts.generate import generate_audio
generate_audio(
text="Bonjour, voici Chatterbox sur MLX !",
model="mlx-community/chatterbox-multilingual-v3",
ref_audio="reference.wav",
lang_code="fr",
file_prefix="output",
)
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Model size
0.7B params
Tensor type
F32
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Hardware compatibility
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Base model
ResembleAI/chatterbox