Hands-on Large Language Models (to be released!)


I am thrilled to introduce a book on Large Language Models that I wrote with Jay Alammar!

With the incredible pace of LLM development, learning about these techniques can be overwhelming. Throughout this book, we take an intuition first approach through visual storytelling with almost 300 custom-made images in the final release.

This book is for those interested in this exciting field. Whether you are a beginner or more advanced, we believe there is something to be found for everyone! When the book is released, we will make all of the code freely available on Github making it easy for you to get started with the inner working of LLMs.

With the current process, we hope to release the book in early September!

🖼️ Visual Storytelling

Over the course of our careers, Jay and I have created educative content in AI with a large focus on illustrations. With the complex and often mathematics-heavy nature of AI, the field quickly becomes overwhelming. By leveraging a visual style of diving into these techniques, we aim to focus on understanding these techniques moreso than writing down the equations that make them up.

Great examples of our visual styles can be found here:

If these styles appeal to you, then you will definitely like this book!

📕 (current) Table of Content

This is the current Table of Content which might change in the upcoming months:

    Part 1 - Theory
  1. Introduction to Language Models
  2. Token Embeddings
  3. Looking Inside Transformer LLMs
  4. Part 2 - Using Pre-Trained Language Models
  5. Text Classification
  6. Text Clustering and Topic Modeling
  7. Prompt Engineering
  8. Advanced Text Generation TEchniques and Tools
  9. Semantic Search and Retrieval Augmented Generation
  10. Multimodal Large Language Models
  11. Part 3 - Training and Fine-Tuning
  12. Creating Text Embedding Models
  13. Fine-Tuning Representation Models for Classification
  14. Fine-Tuning Generation Models