Inside the LLM bundle 
See what’s really happening inside text-generating models... and gain the skills to build and improve them yourself. Start with clear explanations of tokenization, attention, and transformer architectures, then put them to work by coding, pretraining, and fine-tuning a GPT-style model. With this curated collection of four Manning ebooks, you'll be ready to make smarter design decisions, troubleshoot performance, and build more reliable LLM applications. And the technical foundation you'll have built will continue to prove valuable as the field advances.
Build a Large Language Model (From Scratch)
Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself!For deeper understanding and better learning we provide a built-in testing system into liveBook, the online version of this book. Separately, you can download a free PDF Test Yourself guide on this book from here.
How Large Language Models Work
How Large Language Models Work takes you inside an LLM, showing step-by-step how a natural language prompt becomes a clear, readable text completion. Written in plain language, you’ll learn how LLMs are created, why they make errors, and how you can design reliable AI solutions. Along the way, you’ll learn how LLMs “think,” how to design LLM-powered applications like agents and Q&A systems, and how to navigate the ethical, legal, and security issues.
Transformers in Action
Transformers in Action introduces you to transformers and large language models with careful attention to their design and mathematical underpinnings. You’ll learn why architecture matters for speed, scale, and retrieval as you explore applications including RAG and multi-modal models. Along the way, you’ll discover how to optimize training and performance using advanced sampling and decoding techniques, use reinforcement learning to align models with human preferences, and more. The hands-on Jupyter notebooks and real-world examples ensure you’ll see transformers in action as you go.
Deep Learning with Python, Third Edition
Deep Learning with Python, Third Edition makes the concepts behind deep learning and generative AI understandable and approachable. This complete rewrite of the bestselling original includes fresh chapters on transformers, building your own GPT-like LLM, and generating images with diffusion models. Each chapter introduces practical projects and code examples that build your understanding of deep learning, layer by layer.
