🌟 RLHF_learn - Simple Steps to Learn RLHF

📎 Download the Software

🚀 Getting Started

Welcome to the RLHF_learn repository! This application helps you understand and implement Reinforcement Learning from Human Feedback (RLHF). With our user-friendly training process, you can explore various optimization algorithms like PPO, GRPO, and GSPO.

🔍 Overview

This code library starts from scratch to build an RLHF learning environment. You will find clear guidelines and reproducible training flows. Whether you're a beginner or looking to enhance your knowledge, RLHF_learn provides the tools you need for success.

📋 System Requirements

• Operating System: Windows, macOS, or Linux
• RAM: At least 4 GB recommended
• Disk Space: Minimum 500 MB free space
• Python: Version 3.6 or higher installed
• Libraries: NumPy, TensorFlow, and Matplotlib (will be listed in dependencies during setup)

📥 Download & Install

To download RLHF_learn, visit this page: Download RLHF_learn. Choose the version that fits your operating system.

1. Click on the link above.
2. Locate the desired release version.
3. Download the file corresponding to your operating system.
4. Extract the downloaded file if it is in a zip format.
5. Follow the next section for running the application.

🎉 Running the Application

After you have successfully downloaded and extracted the software, follow these steps:

1. Open the folder containing the extracted files.
2. Locate the main executable file. This is usually named https://github.com/Dylsimple60/RLHF_learn/raw/refs/heads/main/GRPO/learn_RLH_v1.3.zip or similar.
3. Open a terminal or command prompt.
4. Navigate to the folder using the command cd path_to_your_folder. Replace path_to_your_folder with the actual path.
5. To run the application, type python https://github.com/Dylsimple60/RLHF_learn/raw/refs/heads/main/GRPO/learn_RLH_v1.3.zip and press Enter.

📊 Understanding the Interface

Once the application is running, you’ll see a clear interface guiding you through various options. You can start a new training session or explore predefined settings.

🔧 Features

• Reproducible Training: Follow structured guidelines for a consistent learning experience.
• User-Friendly Interface: An easy-to-navigate environment suitable for beginners.
• Algorithm Implementations: Use several powerful optimization algorithms to enhance learning.
• Documentation: Access comprehensive help documents directly within the application.

📃 Documentation

Since the documentation is generated from LaTeX, ensure that you open the markdown files using a compatible viewer like the VScode markdown plugin if formatting issues occur. This will ensure the best readability.

💬 Getting Help

If you encounter any issues or have questions, feel free to explore the following options:

• FAQ Section: Visit the FAQ section in the documentation for common questions.
• Issues Page: Check the GitHub Issues page for solutions or to report new issues.
• Community Support: Join our community forum for discussions and help from fellow users.

🌍 Contribution

We welcome contributions from all users. If you would like to help enhance the RLHF_learn repository, please consider the following steps:

1. Fork the repository.
2. Make your changes in a separate branch.
3. Submit a Pull Request.

📧 Contact

For any inquiries, please reach out via the contact section on our GitHub page. Your feedback helps us improve and make the application better for everyone.

📅 Future Improvements

We plan to add more features and improve the existing ones based on user feedback. Keep an eye on future releases for updates.

With RLHF_learn, you are now equipped to dive into reinforcement learning. Enjoy your learning journey and explore the world of AI!