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thelmbook.com is the official website for The Hundred-Page Language Models Book by Andriy Burkov. It serves as the book's information and purchase hub: you'll find the book description, a full chapter list, endorsements from AI figures, author background, and buying options. It's aimed at machine learning practitioners and engineers building text-based applications who want both the theory and working code behind language models.
What the Book Covers
The book builds understanding step by step rather than jumping straight to transformers. According to the site, the progression runs from machine learning fundamentals through count-based language models and recurrent neural networks to modern transformer architectures and large language models. Each concept is paired with mathematical explanations and working Python code.
The site lists these chapters:
| Chapter | Topic |
|---|---|
| Foreword | By Tomáš Mikolov |
| Preface | — |
| 1 | Machine Learning Basics |
| 2 | Language Modeling Basics (with notebooks) |
| 3 | Recurrent Neural Network (with notebook) |
| 4 | Transformers (and beyond, per the excerpt) |
The largest chapter covers large language models, including prompt engineering techniques and how to finetune models to follow arbitrary instructions.
What's Included Beyond the Text
- Complete Python implementations with PyTorch, hosted on GitHub
- Practical Jupyter notebooks for each topic
- Theory, illustrations, and code combined in every chapter
- A free PDF copy if you buy a hardcover
- $150 in free GPU credits on Lambda — claimed by emailing proof of purchase to [email protected]
Who It's For
The site names its audience directly: technical leaders, engineering managers, software developers, data scientists, and machine learning engineers. If you already work with text-based ML applications and want to understand how language models work under the hood — or need to finetune and prompt them reliably — the book is positioned for you. Complete beginners may find the pace brisk given the mathematical grounding.
Buying Options
The site lists three formats:
- E-Book: set your own price
- Hardcover: $65
- Paperback: $47
- Dark Edition: $55
Hardcover buyers can request a free PDF copy. The page does not mention regional availability, shipping terms, or whether the e-book has any access restrictions, so check the purchase page for those details before buying.
Endorsements and Credibility
The book features a foreword by Tomáš Mikolov (known for word2vec and early RNN language modeling work) and back-cover text by Vint Cerf. The site also includes a "What AI Leaders Say" section with endorsements, which you can read in full on the page.
Bottom Line
If you want a compact, code-heavy path from ML basics to transformer-based LLMs — with notebooks you can run and GPU credits to run them on — thelmbook.com gives you the full contents, sample material context, and purchase links in one place. Start with the chapter list to confirm the scope matches your level, then pick a format; the hardcover plus free PDF is the most flexible combination if you want both a physical reference and searchable code-adjacent text.