Hands-On Large Language Models

Explore the world of Large Language Models with over 275 custom made figures in this illustrated guide!

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Reviews

Reviewer 1

Andrew Ng

founder of DeepLearning.AI


"Jay and Maarten have continued their tradition of providing beautifully illustrated and insightful descriptions of complex topics in their new book. Bolstered with working code, timelines, and references to key papers, their book is a valuable resource for anyone looking to understand the main techniques behind how Large Language Models are built. "

Reviewer 2

Nils Reimers

Director of Machine Learning at Cohere | creator of sentence-transformers


"This is an exceptional guide to the world of language models and their practical applications in industry. Its highly-visual coverage of generative, representational, and retrieval applications of language models empowers readers to quickly understand, use, and refine LLMs. Highly recommended! "

Reviewer 3

Josh Starmer

StatQuest


"I can’t think of another book that is more important to read right now. On every single page, I learned something that is critical to success in this era of language models. "

Reviewer 4

Luis Serrano, PhD

Founder and CEO of Serrano Academy


"If you’re looking to get up to speed in everything regarding LLMs, look no further! In this wonderful book, Jay and Maarten will take you from zero to expert in the history and latest advances in large language models. With very intuitive explanations, great real-life examples, clear illustrations, and comprehensive code labs, this book lifts the curtain on the complexities of transformer models, tokenizers, semantic search, RAG, and many other cutting-edge technologies. A must read for anyone interested in the latest AI technology!"

Reviewer 5

Leland McInnes

Researcher at the Tutte Institute for Mathematics and Computing


"Hands-On Large Language Models brings clarity and practical examples to cut through the hype of AI. It provides a wealth of great diagrams and visual aids to supplement the clear explanations. The worked examples and code make concrete what other books leave abstract. The book starts with simple introductory beginnings, and steadily builds in scope. By the final chapters, you will be fine-tuning and building your own large language models with confidence."

Reviewer 6

Prof. DDr. Roman Egger

CEO of Smartvisions.at and Modul University Vienna


"Finally, a book that not only avoids superficial coverage of Large Language Models but also thoroughly explores the background in a way that is both accessible and engaging. The authors have masterfully created a definitive guide that will remain essential reading despite the fast-paced advancements in the field. "

About the Book

Through the visually educational nature of this book and with over 250 custom made figures,
Python developers will learn the practical tools and concepts they need to use Large Language Models today.

Book Image 1 Book Image 2 Book Image 3

Table of Contents

Table of Contents

About the Authors

Jay Alammar is Director and Engineering Fellow at Cohere. Through his popular AI blog, Jay has helped millions of researchers and engineers visually understand machine learning tools and concepts from the basic to the cutting-edge (Transformers, BERT, GPT-3, Stable Diffusion). Jay is also a co-creator of popular machine learning and natural language processing courses on Deeplearning.ai and Udacity.

Maarten Grootendorst is a Senior Clinical Data Scientist at IKNL. He holds two master's degrees in psychology and one in data science, which he leverages to create visual guides in his AI blog. He is the author and maintainer of open source packages (BERTopic, PolyFuzz, KeyBERT) that have been downloaded millions of times and used by data professionals worldwide.

Jay Alammar Maarten Grootendorst