Instructions to use commandeaw/OmniVoice-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use commandeaw/OmniVoice-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir OmniVoice-MLX-4bit commandeaw/OmniVoice-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: apache-2.0 | |
| base_model: k2-fsa/OmniVoice | |
| base_model_relation: quantized | |
| library_name: mlx-audio | |
| pipeline_tag: text-to-speech | |
| tags: | |
| - mlx | |
| OmniVoice in MLX (4bit). For [mlx-audio](https://github.com/Blaizzy/mlx-audio) on Apple Silicon. | |
| ## Usage | |
| ```bash | |
| pip install mlx-audio | |
| python -m mlx_audio.tts.generate \ | |
| --model commandeaw/OmniVoice-MLX-4bit \ | |
| --text "สวัสดีค่ะ ยินดีต้อนรับ" \ | |
| --lang_code th \ | |
| --ref_audio reference.wav | |
| ``` | |
| `--ref_audio` is optional (zero-shot voice cloning); drop it for the default voice. | |
| ## Size | |
| | variant | repo | vs base (fp32) | | |
| |---|---|---| | |
| | bf16 | 1.6 GB | -50% | | |
| | 8bit | 1.1 GB | -68% | | |
| | 4bit | 0.75 GB | -77% | | |