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    HomeLarge Language ModelsFine-Tuning Large Language Models

    Fine-Tuning Large Language Models

    A course by
    Data Science Dojo
    December, 2024 5 lessons English

    In this module, you’ll learn about the core principles of Large Language Models (LLMs), with a focus on fine-tuning and transfer learning. You’ll explore methods like prompt tuning, prefix tuning, and low-rank adaptation, while also learning to evaluate the importance of data quality and domain-specific datasets. By the end, you’ll be equipped to customize and optimize LLMs, through hands-on practice with a Llama2 7B quantized model.

    What you'll learn

    • Analyze the differences between fine-tuning and transfer learning for LLMs.
    • Understand the impact of data quality and domain-specific datasets on model performance.
    • Explore various fine-tuning methods, including full fine-tuning, low-rank adaptation and advanced optimization strategies.
    • Perform fine-tuning on a Llama2 7B quantized model for real-world applications through hands-on experience.

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