Refine Gan V C T K V1 LLM Model

Introduction

RefineGanVCTKV1 is a voice conversion model by SimplCup, trained on the VCTK-Corpus v0.92 (mic1 variant) dataset. The model is designed for tasks involving voice conversion and related applications.

Architecture

The RefineGanVCTKV1 model is based on the RefineGan architecture, optimized for voice conversion tasks. It utilizes a sample rate of 44.1kHz and processes a dataset with a total length of 35 hours.

Training

Epochs: 177
Steps: 1,180,590
Dataset: CSTR-Edinburgh/vctk
Sample Rate: 44.1kHz

Guide: Running Locally

To run the RefineGanVCTKV1 model locally, follow these basic steps:

Clone the Repository:
Clone the Applio repository from GitHub:
```
git clone https://github.com/IAHispano/Applio.git
```
Navigate to the Directory:
Change to the Applio directory:
```
cd Applio
```
Install Dependencies:
Ensure all the necessary dependencies are installed, possibly using a package manager like pip.
Download the Model:
Download the latest version of the model from the Hugging Face model hub.
Run the Model:
Execute the appropriate scripts to start the model for voice conversion tasks.

Suggested Cloud GPUs:
Consider using cloud GPU services like AWS, Google Cloud, or Azure to efficiently run the model, especially if local computational resources are limited.

License

The RefineGanVCTKV1 model is distributed under the OpenRAIL license, allowing for open and collaborative usage and development.

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