---
license: apache-2.0
tags:
- Hibernates
- HVC-Audio-Convert

pipeline_tag: audio-to-audio
---

# HVC-Audio-Convert Base Models

## Overview
These models serve as the foundational components for HVC-Audio-Convert (Soft-VC Voice Conversion), an advanced voice conversion framework that combines SoftVC feature extraction with the VITS (Conditional Variational Autoencoder with Adversarial Learning) architecture.

## Key Features
- High-quality voice conversion capabilities
- Pre-trained on diverse vocal datasets
- Supports cross-lingual voice conversion
- Compatible with HVC-Audio-Convert v4.0 and newer

## Technical Details
- **Architecture**: Based on VITS (Conditional Variational Autoencoder)
- **Feature Extraction**: Hibernates content encoder
- **Training Data**: Curated multi-speaker datasets
- **Model Format**: PyTorch checkpoints

## Usage
1. Download the desired base model
2. Use with HVC-Audio-Convert framework
3. Fine-tune on target voice data
4. Perform voice conversion

## Requirements
- HVC-Audio-Convert framework
- Python 3.8+
- PyTorch 1.13.0+
- CUDA compatible GPU (recommended)

## License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Citation
If you use these models in your research, please cite: