Instructions to use Avdpro/MLX-RVC-Serena-E70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Avdpro/MLX-RVC-Serena-E70 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MLX-RVC-Serena-E70 Avdpro/MLX-RVC-Serena-E70
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
|
Download README.md from Avdpro/MLX-RVC-Serena-E70: direct link, hf CLI and curl.
- Browser
- Download file 970 Bytes
-
https://huggingface.co/Avdpro/MLX-RVC-Serena-E70/resolve/main/README.md
- Command line
-
hf download hf://Avdpro/MLX-RVC-Serena-E70/README.md
-
curl -L -o README.md https://huggingface.co/Avdpro/MLX-RVC-Serena-E70/resolve/main/README.md
970 Bytes
| license: mit | |
| pipeline_tag: audio-to-audio | |
| tags: | |
| - mlx | |
| - voice-conversion | |
| - rvc | |
| # MLX-RVC Serena e70 | |
| Native MLX RVC v2/48 kHz composite checkpoint for AI2Apps. It contains the | |
| MLX-trained e70 synthetic Serena test voice, its exact retrieval index, the | |
| shared ContentVec and RMVPE components, and the converted RVC v2/48 kHz | |
| generator/discriminator initialization used by the native MLX trainer. The | |
| checkpoint contains only safetensors and JSON; it does not require Torch, | |
| torchaudio, FAISS, or pickle at runtime. | |
| The voice training corpus was generated with the `serena` preset of Qwen3-TTS | |
| and is intended as a built-in functional voice, not as the identity of a real | |
| person. Users must have permission to process the source audio they submit. | |
| The implementation is derived from RVC at source revision | |
| `81eed5e8f68b6bed1789f682fe78cdd324495afc`. The selected voice is the native | |
| MLX safe-adaptation epoch-70 checkpoint chosen by listening comparison. | |