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Hands-On Large Language Models
- Author
- Maarten Grootendorst
- Narrator
- Derek Shoales
- Publisher
- Ascent Audio
- Publish Date
- 16 September 2025
- Run Time
- 13 hours 55 minutes
- Format
- Audiobook
What to expect
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 representation; build advanced LLM pipelines to cluster text documents and explore the topics they cover; build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers; explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation; and gain 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 learning.
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Details
- Author
- Maarten Grootendorst
- Narrator
- Derek Shoales
- Duration
- 13 hours 55 minutes
- Release Date
- 16 September 2025
- ISBN
- 9781663754042
- Format
- Audiobook
- Publisher
- Ascent Audio
- Genre
- Machine learning, Natural language and machine translation, Computer science, Database design and theory, Information architecture
Synopsis
AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. With this book, listeners will learn 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 representation; build advanced LLM pipelines to cluster text documents and explore the topics they cover; build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers; explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation; and gain 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 learning.
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