Instructions to use litmudoc/Chatterbox-Multilingual-MLX-v2-Q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use litmudoc/Chatterbox-Multilingual-MLX-v2-Q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Chatterbox-Multilingual-MLX-v2-Q8 litmudoc/Chatterbox-Multilingual-MLX-v2-Q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,531 Bytes
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library_name: mlx-audio
base_model:
- ResembleAI/chatterbox
tags:
- mlx
pipeline_tag: text-to-speech
---
# litmudoc/Chatterbox-Multilingual-MLX-v2-Q8
This model was converted to MLX format from [ResembleAI/chatterbox](https://huggingface.co/ResembleAI/chatterbox) using [mlx-audio](https://github.com/Blaizzy/mlx-audio) version **0.2.10**.
**Note:** This model requires the S3Tokenizer weights from [mlx-community/S3TokenizerV2](https://huggingface.co/mlx-community/S3TokenizerV2), which will be downloaded automatically.
## Use with mlx-audio
```bash
pip install -U mlx-audio
```
### Command line
```bash
curl -L -o ko.wav https://huggingface.co/litmudoc/Chatterbox-Multilingual-MLX-v2-Q8/resolve/main/ko.wav
mlx_audio.tts.generate \
--model litmudoc/Chatterbox-Multilingual-MLX-v2-Q8 \
--text ", μ§λλ¬ μ°λ¦¬λ μ νλΈ μ±λμμ μ΄μμ΅ μ‘°νμλΌλ μλ‘μ΄ μ΄μ νμ λλ¬νμ΅λλ€." \
--lang_code ko \
--ref_audio ko.wav \
--ref_text "μ°λ¦¬λ μ λ§λ‘ νλ¦ν νΈν
μ 묡μμ§λ§, κ·Έλλ ν볡νλ€." \
--verbose --play
```
### Python
```python
from mlx_audio.tts.generate import generate_audio
generate_audio(
text=", μ§λλ¬ μ°λ¦¬λ μ νλΈ μ±λμμ μ΄μμ΅ μ‘°νμλΌλ μλ‘μ΄ μ΄μ νμ λλ¬νμ΅λλ€.",
model="litmudoc/Chatterbox-Multilingual-MLX-v2-Q8",
lang_code="ko",
ref_audio="ko.wav",
ref_text="μ°λ¦¬λ μ λ§λ‘ νλ¦ν νΈν
μ 묡μμ§λ§, κ·Έλλ ν볡νλ€.",
file_prefix="output",
)
```
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