Kokoro-82M ONNX Runtime Inference

This repository contains minimal code and resources for inference using the Kokoro-82M model. The repository supports inference using ONNX Runtime.

Machine learning models rely on large datasets and complex algorithms to identify patterns and make predictions.	Did you know that honey never spoils? Archaeologists have found pots of honey in ancient Egyptian tombs that are over 3,000 years old and still edible!

Features

ONNX Runtime Inference: Kokoro-82M (v0_19) Minimal ONNX Runtime Inference code. It supports en-us and en-gb.

Installation

Clone the repository:

git clone https://github.com/yakhyo/kokoro-82m.git
cd kokoro-82m

Install dependencies:
```
pip install -r requirements.txt
```
Install espeak for text-to-speech functionality: Linux:
```
apt-get install espeak -y
```

Usage

Download ONNX Model

click to download

Jupyter Notebook Inference Example

Run inference using the jupyter notebook:

example.ipynb

CLI Inference

Specify input text and model weights in inference.py then run:

python inference.py

Gradio App

Run below start Gradio App

python app.py

License

This project is licensed under the MIT License. Model weights licensed under the Apache 2.0

Acknowledgments

https://huggingface.co./hexgrad/Kokoro-82M