Test Yourself on Sebastian Raschka's Build a Large Language Model (From Scratch)

300+ practice problems to cement your learning

Curated from Build a Large Language Model (From Scratch)

• Publisher: Manning
• Year: 2025
• eBook ISBN: 9781638357629
• Edition: 0
• Subtopic: Neural Networks

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!

Sebastian Raschka’s bestselling book Build a Large Language Model (From Scratch) is the best way to learn how Large Language Models function. It uses Python and the PyTorch deep learning library. It’s a unique way to learn this subject, which some believe is the only way to truly learn: you build a model yourself.

Even with the clear explanations, diagrams, and code in the book, learning a complex subject is still hard. This Test Yourself guide intends to make it a little easier. The structure mirrors the structure of Build a Large Language Model (From Scratch), focusing on key concepts from each chapter. You can test yourself with multiple-choice quizzes, questions on code and key concepts, and questions with longer answers that push you to think critically. The answers to all questions are provided.

Depending on what you know at any point, this Test Yourself guide can help you in different ways. It will solidify your knowledge if used after reading a chapter. But it will also benefit you if you digest it before reading. By testing yourself on the main concepts and their relationships you are primed to navigate a chapter more easily and be ready for its messages.

We recommend using it before and after reading, as well as later when you have started forgetting. Repeated learning solidifies our knowledge and integrates it with related knowledge already in our long-term memory.

What's inside

• Questions on code and key concepts
• Critical thinking exercises requiring longer answers
• Answers for all questions

About the reader

For readers of Build a Large Language Model (From Scratch) who want to enhance their learning with exercises and self-assessment tools.

About the author

Curated from Build a Large Language Model (From Scratch)

Table of contents

• copyright
• contents
• brief contents
• introduction
• 1 Understanding large language models
• 2 Working with text data
• 3 Coding Attention Mechanisms
• 4 Implementing a GPT model from scratch to generate text
• 5 Pretraining on unlabeled data
• 6 Fine-tuning for classification
• 7 Fine-tuning to follow instructions
• Appendix A. Introduction to PyTorch
• Appendix B. References and further reading
• Appendix C. Exercise solutions
• Appendix D. Adding bells and whistles to the training loop
• Appendix E. Parameter-efficient fine-tuning with LoRA