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Build a Large Language Model (From Scratch)

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Build a Large Language Model (From Scratch)

著者: Sebastian Raschka
ナレーター: Julie Brierley
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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.

This book 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 LLMBuild 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 book: This 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!

About the listener: Listeners 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.

About the author: Sebastian Raschka is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2024 Manning Publications (P)2024 Manning Publications
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