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Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!
In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.
Build a Large Language Model (from Scratch) teaches you how to:
Plan and code all the parts of an LLM
Prepare a dataset suitable for LLM training
Fine-tune LLMs for text classification and with your own data
Use human feedback to ensure your LLM follows instructions
Load pretrained weights into an LLM
Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.
About the technology:
Physicist Richard P. Feynman reportedly said, “I don’t understand anything I can’t build.” Based on this same powerful principle, bestselling author Sebastian Raschka guides you step by step as you build a GPT-style LLM that you can run on your laptop. This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning.
About the book:
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!
What's inside:
Plan and code an LLM comparable to GPT-2
Load pretrained weights
Construct a complete training pipeline
Fine-tune your LLM for text classification
Develop LLMs that follow human instructions
About the reader:
Readers need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs.
Build a Large Language Model (From Scratch) is for machine learning enthusiasts, engineers, researchers, students, and practitioners who want to gain a deep understanding of how LLMs work and learn to build their own models from scratch. Both beginners and experienced developers will be able to use their existing skills and knowledge to grasp the concepts and techniques used in creating LLMs.
About the author:
Sebastian Raschka is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software.
The technical editor on this book was David Caswell.
Understanding large language models
Working with text data
Coding attention mechanisms
Implementing a GPT model from scratch to generate text
Pretraining on unlabeled data
Fine-tuning for classification
Fine-tuning to follow instructions
Introduction to PyTorch
References and further reading
Exercise solutions
Adding bells and whistles to the training loop