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Hands-On Large Language Models: Language Understanding and Generation (True PDF)

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English | October 15th, 2024 | ISBN: 1098150961 | 428 pages | True PDF | 18.39 MB



AI
has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep
learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise
of new features, products, and entire industries. With this book, Python developers will learn the practical tools and
concepts they need to use these capabilities today.

You'll learn how to use the power of pre-trained large
language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword
matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text
documents; and use existing libraries and pre-trained models for text classification, search, and clusterings.

This book also shows you how to
• Build advanced LLM pipelines to cluster text documents and explore the topics
they belong to
• Build semantic search engines that go beyond keyword search with methods like dense retrieval
and rerankers
• Learn various use cases where these models can provide value
• Understand the architecture
of underlying Transformer models like BERT and GPT
• Get a deeper understanding of how LLMs are trained
•
Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model
fine-tuning, contrastive fine-tuning, in-context learning, etc.)

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