Fine Tuning LLM Models – Generative AI Course
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3 months ago
Published on May 21, 2024
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Table of Contents
Title: Fine Tuning LLM Models – Generative AI Course Channel: freeCodeCamp.org
Description: Learn how to fine-tune LLM models. This course covers fine-tuning using QLORA and LORA, as well as quantization using LLama2, Gradient, and the Google Gemma model. The crash course includes theoretical and practical instructions to help you understand how to perform fine-tuning.
Tutorial:
- Introduction (0:00:00):
- Start by watching the introduction to understand the basics of fine-tuning LLM models.
- Quantization Intuition (0:01:39):
- Dive into the concept of quantization to gain a better understanding of how it works in fine-tuning LLM models.
- Lora And QLORA In-depth Intuition (0:34:03):
- Learn about Lora and QLORA in detail to grasp their significance in fine-tuning LLM models.
- Fine-tuning With LLama2 (0:56:26):
- Follow the tutorial to fine-tune LLM models using LLama2 and understand the process step by step.
- 1 bit LLM In-depth Intuition (1:20:35):
- Explore the 1 bit LLM model in-depth to enhance your knowledge of fine-tuning techniques.
- Fine-tuning with Google Gemma Models (1:37:33):
- Learn how to fine-tune LLM models using Google Gemma models and the implications of this approach.
- Building LLM Pipelines With No Code (1:59:45):
- Discover how to build LLM pipelines without writing any code and simplify the fine-tuning process.
- Fine-tuning With Own Custom Data (2:20:33):
- Finally, learn how to fine-tune LLM models with your own custom data for personalized results.
Additional Resources:
- Access the code for fine-tuning LLM models on GitHub: https://github.com/krishnaik06/Finetuning-LLM
- Course developed by @krishnaik06
By following these steps and instructions from the video, you will gain a comprehensive understanding of fine-tuning LLM models and be able to apply these techniques in your own projects effectively.