Fine-Tune Your LLMs

Fine-Tune Your LLMs

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 14m | 188 MB

In this course, award-winning tech innovator and AI/ML leader Kesha Williams guides you through several concepts and techniques that you can use to fine-tune LLMs using your own data. Explore the concepts and costs of fine-tuning and learn how to set up your environment for it. Go over the steps to prepare your data and fine-tune a pre-trained LLM. Plus, practice evaluating and iterating a fine-tuned model. Practical, hands-on challenges in each chapter give you a chance to deepen your understanding of the topics.

Table of Contents

1 Introduction to fine-tuning LLMs
2 Review the fine-tuning project

Exploring Concepts and Costs of Fine-Tuning
3 Explore LLMs
4 Review the fine-tuning process
5 Understand the costs of fine-tuning

Setting up Your Environment for Fine-Tuning
6 Explore the OpenAI API for fine-tuning
7 Use GitHub codespaces
8 Sign up for an OpenAI account

Preparing Data for Fine-Tuning
9 Source data for fine-tuning
10 Challenge Source data for fine-tuning
11 Solution Source data for fine-tuning
12 Prepare data for fine-tuning
13 Challenge Prepare and upload data for fine-tuning
14 Solution Prepare and upload data for fine-tuning

Fine-Tuning a Pretrained LLM
15 Train a new fine-tuned model
16 Challenge Fine-tune a pretrained LLM
17 Solution Fine-tune a pretrained LLM
18 Retrieve and use a fine-tuned model
19 Challenge Develop a chatbot based on a fine-tuned model
20 Solution Develop a chatbot based on a fine-tuned model

Evaluating a Fine-Tuned Model
21 Evaluate a fine-tuned model
22 Iterate a fine-tuned model
23 Challenge Evaluate a fine-tuned model
24 Solution Evaluate a fine-tuned model

25 Your fine-tuning journey