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GitHub - instructlab/instructlab: Command-line interface. Use this to chat with the model or train the model (training consumes the taxonomy data)

May 07, 2024 - github.com
The markdown data provides a comprehensive guide on how to use InstructLab, a Command-Line Interface (CLI) tool that allows users to download, chat with, and add new knowledge and skills to a pre-trained Large Language Model (LLM). The guide includes instructions on how to install and initialize InstructLab, download the model, serve the model, chat with the model, and contribute new knowledge or skills. It also provides details on how to generate a synthetic dataset, train the model, test the newly trained model, and submit new knowledge or skills.

The guide also mentions that InstructLab uses a novel synthetic data-based alignment tuning method for Large Language Models (LLMs). It is optimized to enable community members with modest hardware to use the technique. However, if users have more sophisticated hardware, they can configure InstructLab to use a larger teacher model to achieve higher-fidelity results. The guide also provides instructions on how to troubleshoot and contribute to the InstructLab CLI.

Key takeaways:

  • InstructLab is a Command-Line Interface (CLI) tool that allows users to download a pre-trained Large Language Model (LLM), chat with the LLM, and add new knowledge and skills to the pre-trained LLM.
  • The tool uses a novel synthetic data-based alignment tuning method for Large Language Models (LLMs). The "lab" in InstructLab stands for Large-Scale Alignment for ChatBots.
  • Users can contribute new knowledge or compositional skills to their local taxonomy repository, generate a synthetic dataset based on the newly added knowledge or skill set, and then re-train the LLM with the new training data.
  • The tool has been optimized to enable community members with modest hardware to use the technique. However, users with more sophisticated hardware can configure InstructLab to use a larger teacher model to achieve higher-fidelity results.
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