JPT (Java Pre-trained Transformer)

Welcome to the JPT project! This repository contains a Java implementation of a pre-trained transformer model.

Table of Contents

• About
• Features
• Technologies Used
• Installation
• Usage
• Updating
• Contributing
• License

About

JPT is a Java-based project that leverages pre-trained transformer models for natural language processing tasks. The goal is to provide a robust and scalable solution for integrating transformer models in Java applications.

Features

• Integration with GPT models
• Easy setup and configuration
• Pre-configured environment for development
• Supports custom configuration files

Technologies Used

• Java: The primary programming language used for developing the API.
• Gradle: Used for building and managing project dependencies.
• MySQL: Database server for storing application data.
• Pre-trained Transformer Models: Leveraging models like GPT for NLP tasks.

Installation

To install and set up the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/serezk4/JPT.git

2. Navigate to the project directory:

   cd JPT

3. Set up your configuration files in src/main/resources/:
   • application.properties
   • telegram.properties
   • gpt.properties
4. Ensure you have the required environment setup:
   • JDK 21
   • MySQL Server
5. Build the bootable JAR file:

   gradle bootJar

Usage

To run the project, execute the following command after setting up the environment and building the project:

java -jar build/libs/JPT-0.1.0.jar

Updating

To update the project, navigate to your local repository and pull the latest changes:

git pull origin master

Contributing

We welcome contributions to improve JPT. To contribute, follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit them (git commit -m 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Open a Pull Request.

Please ensure your code adheres to the project's coding standards and includes appropriate tests.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Feel free to explore, use, and contribute to EljurApi. If you have any questions or need further assistance, please open an issue on GitHub.

Happy coding!