Instructions to use Avdpro/MLX-Seed-VC-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Avdpro/MLX-Seed-VC-v2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MLX-Seed-VC-v2 Avdpro/MLX-Seed-VC-v2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
MLX Seed-VC v2
Torch-free native MLX conversion of the pinned Seed-VC v2 inference pipeline for AI2Apps. The composite checkpoint contains the CFM and AR models, both ASTRAL quantizers, CAMPPlus, HuBERT Large layer 18, and BigVGAN v2. Runtime weights are stored as safetensors and configuration as JSON.
The default quality profile uses timbre mode with 30 diffusion steps. A 10-step fast profile and a 30-step AR voice profile are also exposed by the Model Package. A request must contain both source audio and reference-speaker audio; reference audio is request-scoped and is not persisted as a Voice Profile.
The implementation is based on Plachtaa/seed-vc revision
51383efd921027683c89e5348211d93ff12ac2a8. See NOTICE.md for all pinned
checkpoint sources and licenses.
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