Hands-On-Large-Language-Models
HandsOnLLM/Hands-On-Large-Language-Models
Code repository for Hands-On Large Language Models
Overview
This repository contains the code and Jupyter Notebook examples from Jay Alammar and Maarten Grootendorst’s O'Reilly publication 'Hands-On Large Language Models', providing practical insights into using Large Language Models.
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Install
git clone https://github.com/HandsOnLLM/Hands-On-Large-Language-ModelsREADME
Hands-On Large Language Models
Welcome! In this repository you will find the code for all examples throughout the book Hands-On Large Language Models written by Jay Alammar and Maarten Grootendorst which we playfully dubbed:
"The Illustrated LLM Book"
Through the visually educational nature of this book and with almost 300 custom made figures, learn the practical tools and concepts you need to use Large Language Models today!
The book is available on:
Table of Contents
We advise to run all examples through Google Colab for the easiest setup. Google Colab allows you to use a T4 GPU with 16GB of VRAM for free. All examples were mainly built and tested using Google Colab, so it should be the most stable platform. However, any other cloud provider should work.
| Chapter | Notebook |
|---|---|
| Chapter 1: Introduction to Language Models | |
| Chapter 2: Tokens and Embeddings | |
| Chapter 3: Looking Inside Transformer LLMs | |
| Chapter 4: Text Classification | |
| Chapter 5: Text Clustering and Topic Modeling | |
| Chapter 6: Prompt Engineering | |
| Chapter 7: Advanced Text Generation Techniques and Tools | |
| Chapter 8: Semantic Search and Retrieval-Augmented Generation | |
| Chapter 9: Multimodal Large Language Models | |
| Chapter 10: Creat |