Build a Large Language Model (From Scratch) Paperback – 1 Nov. 2024

The most helpful and inspirational NLP book I've read. (I'm currently just over 1/2 way through.) It's lucid and easy to follow for anyone with intermedia Python skills and a basic understanding of NLP. Raschka anticipates what you need to know at any given stage. I did an MSc in NLP/SP a couple of years ago and we went through a lot of these topics and similar code sequences then. But reading this has bedded it all down and helped me to understand how train my own models in the future. Looking forward to reading his upcoming book on reasoning models after I finish this.

I’ve just finished the first two chapters of Build a Large Language Model from Scratch by Sebastian R. So far, it’s an excellent read. The book provides a solid understanding and clear insights into how large language models (LLMs) work, including their underlying architecture.What I particularly appreciate is how approachable it is for readers who don’t have a background in AI. If you’re curious about LLMs and want to get a deeper grasp of how they function—without getting overwhelmed—this is a great starting point. I’d definitely recommend it to anyone interested in AI, regardless of their technical background

Yes, this is an extraordinarily well written book about how to build an LLM. The language is friendly and easy to understand. Each step is profoundly explained. On top, it is absolutely clear that the author loves his work and provides a positive attitude in tackling such a model. I highly recommend this book, it opens all doors into the profound knowledge about LLMs.

Truly great and exceptionally well thought out resource for learning how LLMs work. Don’t even think twice and read it, study the great examples, look up bonus materials and check out accompanying YT videos from S. Raschka. I wish all tech books were at this quality level!

Excellent Book - really does show how to make a LLM from scratch as the title suggests.

Received in good condition

Explains transformer architecture clearly and its implementation, which is a backbone of LLMs. The book also delves into practical aspects of building and training large language models, providing hands-on examples and code snippets. It's an invaluable resource for anyone looking to understand the intricacies of LLMs from the ground up. However, if you need to further develop LLMs in a real-world setting, be aware that this book is aimed at building the foundations. You will need to read additional books that cover the implementation of systems required to deploy LLMs