(If you downloaded the code bundle from the Manning website, please consider visiting the official code repository on GitHub at https://github.com/rasbt/LLMs-from-scratch.)
In Build a Large Language Model (from Scratch), you'll discover how LLMs work from the inside out. In this book, I'll guide you step by step through creating your own LLM, explaining each stage with clear text, diagrams, and examples.
The method described in this book for training and developing your own small-but-functional model for educational purposes mirrors the approach used in creating large-scale foundational models such as those behind ChatGPT.
- Link to the official source code repository
- Link to the early access version at Manning
- ISBN 9781633437166
- Publication in Early 2025 (estimated)
Please note that the Readme.md file is a Markdown (.md) file. If you have downloaded this code bundle from the Manning website and are viewing it on your local computer, I recommend using a Markdown editor or previewer for proper viewing. If you haven't installed a Markdown editor yet, MarkTexthttps://www.marktext.cc is a good free option.
Alternatively, you can view this and other files on GitHub at https://github.com/rasbt/LLMs-from-scratch.
| Chapter title | Main code (for quick access) | All code + supplementary |
|---|---|---|
| Ch 1: Understanding Large Language Models | No code | No code |
| Ch 2: Working with Text Data | - ch02.ipynb - dataloader.ipynb (summary) - exercise-solutions.ipynb |
./ch02 |
| Ch 3: Coding Attention Mechanisms | - ch03.ipynb - multihead-attention.ipynb (summary) |
./ch03 |
| ... | ... | ... |
| Appendix A: Introduction to PyTorch | - code-part1.ipynb - code-part2.ipynb - DDP-script.py - exercise-solutions.ipynb |
./appendix-A |
(A mental model summarizing the contents covered in this book.)