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Build a Large Language Model (From Scratch)
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Build a Large Language Model (From Scratch)

Book Details

Format Hardback or Cased Book
ISBN-10 1633437167
ISBN-13 9781633437166
Publisher Manning Publications
Imprint Manning Publications
Country of Manufacture GB
Country of Publication GB
Publication Date Nov 1st, 2024
Print length 368 Pages
Weight 668 grams
Dimensions 23.40 x 18.80 x 2.30 cms
Ksh 8,300.00
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Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!
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.

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