Large Language Models: An Illustrated Guide
Hello!
What this book IS
A book focused on examples and figures to explain how Language Modeling started and how we got to where we are today.
A technical book aimed at people with some mathematical and some programming knowledge.
What this book is NOT
A reference for how to implement an LLM at the code level. Read Build a Large Language Model From Scratch by Sebastian Raschka instead;
A book with extensive mathematical proofs of the statistical and algebraic components of LLMs (not sure there is any good source here other than the original papers themselves);
A book on tools and frameworks to work with LLMs (Pytorch, Tensorflow, Huggingface, etc).
A general book about NLP. Read Speech and Language Processing by Dan Jurafsky and James H. Martin.
A book on how to deal with problems introduced by LLMs: hallucinations, jailbreaking, bias, existential risks, etc.
A book on the empirical techniques and hacks to make LLMs work better at scale.
A book on the technicals of putting LLM-enabled systems to use in products and organizations.
A comprehensive reference on how Reinforcement Learning is applied to fine-tune LLMs. Read the RLHF Book by Nathan Lambert and watch Lectures 1-10 on [Stanford CS224R Deep Reinforcement Learning].
Acknowledgements
My family and my dog Zulu: For support throughout my life.
Alan Watts: The person who’s had the biggest spiritual influence on my life. Buy his books on Amazon
Aaron Clarey: Thanks for all the advice and hard truths delivered. Buy Aaron’s books on Amazon and subscribe to his Youtube channel