Build a Large Language Model (From Scratch)

Sebastian Raschka

ISBN 10: 1633437167 / ISBN 13: 9781633437166

Editore: Manning Publications, US, 2024

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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 LLMPrepare a dataset suitable for LLM trainingFine-tune LLMs for text classification and with your own dataUse human feedback to ensure your LLM follows instructionsLoad 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.

Codice articolo LU-9781633437166

Dati bibliografici

• Titolo: Build a Large Language Model (From Scratch)
• Editore: Manning Publications, US
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 1633437167
• ISBN 13: 9781633437166
• Rilegatura: Hardback
• Condizione: New
• Dimensioni: 18,73 L x 1,78 A x 23,5 P centimetri 18,73 centimetri di larghezza per 1,78 centimetri di altezza per 23,5 centimetri di profondità
• Peso: 673 grammi

Descrizione articolo

Riassunto

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), you’ll discover how LLMs work from the inside out. In this insightful book, bestselling author Sebastian Raschka guides you step by step through creating your own LLM, explaining each stage with clear text, diagrams, and examples. You’ll go from the initial design and creation to pretraining on a general corpus, all the way to finetuning 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
• Finetune LLMs for text classification and with your own data
• Apply instruction tuning techniques to ensure your LLM follows instructions
• Load pretrained weights into an LLM

The large language models (LLMs) that power cutting-edge AI tools like ChatGPT, Bard, and Copilot seem like a miracle, but they’re not magic. This book demystifies LLMs by helping you build your own from scratch. You’ll get a unique and valuable insight into how LLMs work, learn how to evaluate their quality, and pick up concrete techniques to finetune and improve them.

The process you use to train and develop your own small-but-functional model in this book follows the same steps used to deliver huge-scale foundation models like GPT-4. Your small-scale LLM can be developed on an ordinary laptop, and you’ll be able to use it as your own personal assistant.

Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications.

About the book

Build a Large Language Model (from Scratch) is a one-of-a-kind guide to building your own working LLM. In it, machine learning expert and author Sebastian Raschka reveals how LLMs work under the hood, tearing the lid off the Generative AI black box. The book is filled with practical insights into constructing LLMs, including building a data loading pipeline, assembling their internal building blocks, and finetuning techniques. As you go, you’ll gradually turn your base model into a text classifier tool, and a chatbot that follows your conversational instructions.

About the reader

For readers who know Python. Experience developing machine learning models is useful but not essential.

About the author

Sebastian Raschka has been working on machine learning and AI for more than a decade. Sebastian joined Lightning AI in 2022, where he now focuses on AI and LLM research, developing open-source software, and creating educational material. Prior to that, Sebastian worked at the University of Wisconsin-Madison as an assistant professor in the Department of Statistics, focusing on deep learning and machine learning research. He has a strong passion for education and is best known for his bestselling books on machine learning using open-source software.

Informazioni sull?autore

Sebastian Raschka has been working on machine learning and AI for more than a decade. Sebastian joined Lightning AI in 2022, where he now focuses on AI and LLM research, developing open-source software, and creating educational material. Prior to that, Sebastian worked at the University of Wisconsin-Madison as an assistant professor in the Department of Statistics, focusing on deep learning and machine learning research. He has a strong passion for education and is best known for his bestselling books on machine learning using open-source software.