000			02931nam a22002897a 4500
003			OSt
005			20260520164311.0
008			260428b |||||||| |||| 00| 0 eng d
020			_a9789355425522
041			_aeng
082			_a006.35 ALA-H
100			_aAlammar, Jay _976787
245			_aHands-on large language models _b: language understanding and generation
260			_aNavi Mumbai _bShroff Publishers & Distributors Pvt. Ltd. _c2025
300			_axix, 403 pages : illustrations ; 24 cm
520			_aAI 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. Through his book's visually educational nature, readers will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained 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 ; 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 Content notes Part 1. Understanding language models. An introduction to Large Language Models -- Tokens and embeddings -- Looking inside Large Language Models -- Part 2. Using pretrained language models. Text classification -- Text clustering and topic modeling -- Prompt engineering -- Advanced text generation techniques and tools -- Semantic search and retrieval-augmented generation -- Mulitimodal Large Language Models -- Part 3. Training and fine-tuning language models. Creating text embedding models -- Fine-tuning representation models for classification -- Fine-tuning generation models
650			_aArtificial intelligence _xComputer programs _979358
650			_aNatural language processing (Computer science) _979359
650			_aLarge Language Models _979360
650			_aSoftware engineering _979361
650			_aArtificial intelligence _xEngineering applications _979362
650			_aGenerative programming (Computer science) _979363
650			_aApplication software _xDevelopment _979364
700			_aGrootendorst, Maarten _976795
942			_cBK
999			_c200000 _d200000