Hands-On Large Language Models: Language Understanding and Generation

by: Jay Alammar (Author),Maarten Grootendorst(Author)

Publisher: O’Reilly Media

Edition: 1st

Publication Date: 2024/10/15

Language: English

Print Length: 425 pages

ISBN-10: 1098150961

ISBN-13: 9781098150969

Book Description

AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep leaing, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through this book’s visually educational nature, readers will lea practical tools and concepts they need to use these capabilities today. You’ll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of Transformer language models that excel at text generation and representationBuild advanced LLM pipelines to cluster text documents and explore the topics they coverBuild semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankersExplore how generative models can be used, from prompt engineering all the way to retrieval-augmented generationGain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context leaing

About the Author

AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep leaing, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through this book’s visually educational nature, readers will lea practical tools and concepts they need to use these capabilities today. You’ll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of Transformer language models that excel at text generation and representationBuild advanced LLM pipelines to cluster text documents and explore the topics they coverBuild semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankersExplore how generative models can be used, from prompt engineering all the way to retrieval-augmented generationGain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context leaing