Gain insights into fine-tuning LLMs with LoRA and QLoRA. Explore parameter-efficient methods, LLM quantization, and hands-on exercises to adapt AI models with minimal resources efficiently.
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Overview
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This hands-on course will teach you the art of fine-tuning large language models (LLMs). You will also learn advanced techniques like Low-Rank Adaptation (LoRA) and Quantized Low-Rank Adaptation (QLoRA) to customize models such as Llama 3 for specific tasks. The course begins with fundamentals, exploring fine-tuning, the types of fine-tuning, comparison with pretraining, discussion on retrieval-augmented generation (RAG) vs. fine-tuning, and the importance of quantization for reducing model size while maintaining performance.
Gain practical experience through hands-on exercises using quantization methods like int8 and bits and bytes. Delve into parameter-efficient fine-tuning (PEFT) techniques, focusing on implementing LoRA and QLoRA, which enable efficient fine-tuning using limited computational resources.
After completing this course, you’ll master LLM fine-tuning, PEFT fine-tuning, and advanced quantization parameters, equipping you with the expertise to adapt and optimize LLMs for various applications.
This hands-on course will teach you the art of fine-tuning large language models (LLMs). You will also learn advanced techniques...Show More
WHAT YOU'LL LEARN
A solid foundation in fine-tuning LLMs, including practical techniques for Llama 3 fine-tuning and broader LLM fine-tuning workflows
Familiarity with LLM quantization methods, such as int8 quantization and bits and bytes quantization, for reducing model size and improving deployment efficiency
Hands-on experience implementing quantization techniques and optimizing models for performance and efficiency
An understanding of Low-Rank Adaptation (LoRA) and Quantized Low-Rank Adaptation (QLoRA) as key approaches for parameter-efficient fine-tuning (PEFT)
Hands-on experience fine-tuning Llama 3 model with custom datasets, using PEFT fine-tuning techniques for real-world applications
A solid foundation in fine-tuning LLMs, including practical techniques for Llama 3 fine-tuning and broader LLM fine-tuning workflows
Show more
Content
13 Lessons2 Quizzes
1.
Getting Started
1 Lessons
Get familiar with fine-tuning LLMs using LoRA and QLoRA with practical insights.
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