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Fine-Tuning Your Own Llama 3 Model

Maxime, one of the world's leading thinkers in generative AI research, shows you how to fine-tune the Llama 3 LLM using Python and the Hugging Face platform.
Maxime Labonne
Maxime Labonne

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실습 문제하고 트랙하세요.

Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

Meta's Llama 3 is one of the most powerful open weights LLMs, and forms the basis of many commercial generative AI applications. Fine-tuning is a technique to get better performance from LLMs for specific use cases, and is fast becoming an essential skill for organizations making AI applications.

In this session, Maxime, one of the world's leading thinkers in generative AI research, shows you how to fine-tune the Llama 3 LLM using Python and the Hugging Face platform. You'll take a stock Llama 3 LLM, process data for training, then fine-tune the model, and evaluate its performance for an industry use case.

Key Takeaways:

  • Learn how to use Hugging Face Python packages to fine-tune LLMs.
  • Understand the workflow for customizing LLMs by fine-tuning.
  • Learn how to evaluate the success of your fine-tuned model.

Resources (including link to notebook)

주제

Artificial IntelligenceGenerative AIPython

관련

튜토리얼

Fine-Tuning Llama 3 and Using It Locally: A Step-by-Step Guide

Fine-Tune Llama 3.2

튜토리얼

Fine-tuning Llama 3.2 and Using It Locally: A Step-by-Step Guide

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