Könyv Build a Large Language Model (from Scratch) Sebastian Raschka

Build a Large Language Model (from Scratch)

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten alacsony példányszámban
Küldés 9-15 napon belül
21 295 Ft
Learn how to create, train, and tweak large language models (LLMs) by building one from the ground u...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2024
oldal
368
EAN
9781633437166
ISBN
1633437167
Enbook ID
46056803
Súly
624
Méretek
188 x 234 x 23

Teljes leírás

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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