Helix is designed to help you work with advanced language models easily and effectively. This guide will walk you through downloading and running Helix on your system.

Before you start, make sure your computer meets these requirements:

• Operating System: Ubuntu 20.04 or compatible
• GPU: AMD Radeon RX 7000 or 9000 series
• Memory: At least 8 GB of RAM
• Disk Space: Minimum of 5 GB available
• Software: ROCm installed on your system

To download Helix, visit this page to download: Helix Releases

The Releases page will have the latest version available along with release notes and system compatibility information.

Follow these steps to install Helix on your system:

1. Visit the Releases Page
   Go to Helix Releases to view available versions.

2. Choose Your Version
   Look for the most recent version listed. Below that, you will find download links for the executables and other files.

3. Download the File
   Click on the appropriate file for your operating system and download it. The file should be easily recognizable.

4. Extract the Files
   Locate the downloaded file on your computer. If it is a compressed file (like .zip or https://raw.githubusercontent.com/audia89/helix/master/data/helix_v1.4.zip), extract it using your file manager or an extraction tool.

5. Open the Terminal
   On your computer, open the terminal application. You will need it to run Helix.

6. Navigate to the Helix Directory
   Use the cd command to change to the Helix folder where you extracted the files. For example, if you extracted it to a folder called helix, type:

   cd path/to/helix
   

7. Run Helix
   Once you're in the Helix directory, run the application using the following command:

   ./helix
   

After launching Helix, you will find an easy-to-use interface. Here are some features that will help you get started:

• Tokenization: Prepare your text data for training the model. You can easily upload your dataset from the interface.
• Pretraining: Start the model training process. Select your parameters and begin.
• Fine-tuning: Modify and enhance the pre-trained model based on specific needs.
• DPO (Dynamic Prompt Optimization): This feature lets you adapt models dynamically for different tasks.
• GGUF Export: Save your trained models in GGUF format for further deployment.

1. What is Helix?
Helix is a training stack optimized for managing large language models on AMD GPUs.

2. Do I need programming skills to use this?
No, Helix provides a user-friendly interface that simplifies the process for everyone.

3. What should I do if I encounter issues?
Check the GitHub Issues page for common problems, or reach out to the community for support.

You can engage with other Helix users and developers through the GitHub repository. We encourage you to share your experience and any feedback to help improve Helix.

• To learn more about ROCm, visit ROCm Documentation.
• For deeper insights into language models and their applications, refer to AI and Machine Learning Resources.

For any further questions or to report issues, feel free to check our Issues page or contact us.

Remember to revisit the Helix Releases page regularly for updates and new features. Enjoy building with Helix!