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lexandstuff/
rvc-mlx-weights

Name: rvc-mlx-weights
Availability: InStock

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RVC-MLX Pretrained Weights

MLX-compatible pretrained weights for RVC (Retrieval-based Voice Conversion), converted for use with rvc-mlx.

These weights enable high-quality voice conversion on Apple Silicon Macs using the MLX framework.

Available Models

File	Sample Rate	Size	Description
`v2/f0G48k.safetensors`	48 kHz	110 MB	V2 with F0 (pitch) - highest quality
`v2/f0G40k.safetensors`	40 kHz	105 MB	V2 with F0 (pitch)
`v2/f0G32k.safetensors`	32 kHz	107 MB	V2 with F0 (pitch)

All models use:

Architecture: SynthesizerTrnMs768NSFsid
Input: 768-dim ContentVec features
F0 Support: Yes (pitch-aware synthesis)

Quick Start

python

from huggingface_hub import hf_hub_download

# Download the 48kHz model
weights_path = hf_hub_download(
    repo_id="lexandstuff/rvc-mlx-weights",
    filename="v2/f0G48k.safetensors"
)

# Download config
config_path = hf_hub_download(
    repo_id="lexandstuff/rvc-mlx-weights",
    filename="v2/config.json"
)

Usage with rvc-mlx

python

import json
from safetensors.numpy import load_file
from rvc_mlx.models import SynthesizerTrnMs768NSFsid

# Load config
with open(config_path) as f:
    configs = json.load(f)
    config = configs["48000"]  # or "40000", "32000"

# Create model
model = SynthesizerTrnMs768NSFsid(**config)

# Load weights
weights = load_file(weights_path)
# ... load weights into model

Model Details

These are inference-only weights - training components (posterior encoder) have been removed to reduce file size.

Architecture

SynthesizerTrnMs768NSFsid
├── enc_p (TextEncoder)      - Encodes ContentVec + pitch
├── flow (ResidualCoupling)  - Normalizing flow for voice conversion
├── dec (GeneratorNSF)       - HiFi-GAN vocoder with neural source filter
└── emb_g (Embedding)        - Speaker embedding

Upsampling Rates

Sample Rate	Upsample Rates	Total Factor
32 kHz	[10, 8, 2, 2]	320x
40 kHz	[10, 10, 2, 2]	400x
48 kHz	[12, 10, 2, 2]	480x

Original Source

These weights are converted from the official RVC pretrained models:

Source: lj1995/VoiceConversionWebUI
Files: pretrained_v2/f0G{32k,40k,48k}.pth

License

MIT License - same as the original RVC project.

Citation

If you use these weights, please cite the original RVC project:

bibtex

@software{rvc2023,
  author = {RVC-Project},
  title = {Retrieval-based-Voice-Conversion-WebUI},
  year = {2023},
  url = {https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI}
}