Hands-on large language models (Record no. 200000)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02931nam a22002897a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260520164311.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260428b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789355425522 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.35 ALA-H |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Alammar, Jay |
| 245 ## - TITLE STATEMENT | |
| Title | Hands-on large language models |
| Remainder of title | : language understanding and generation |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Navi Mumbai |
| Name of publisher | Shroff Publishers & Distributors Pvt. Ltd. |
| Year of publication | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xix, 403 pages : illustrations ; 24 cm |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. 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<br/>Content notes<br/>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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence |
| General subdivision | Computer programs |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Natural language processing (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Large Language Models |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Software engineering |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence |
| General subdivision | Engineering applications |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Generative programming (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Application software |
| General subdivision | Development |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Grootendorst, Maarten |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books and Monographs |
| Full call number | Accession Number | Koha item type | Lost status | Damaged status | Permanent Location | Current Location | Shelving location | Date acquired | Source of acquisition |
|---|---|---|---|---|---|---|---|---|---|
| 006.35 ALA-H | 102739 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 27.04.2026 | Mumbai, TV Enterprises | ||
| 006.35 ALA-H | 102824 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.35 ALA-H | 102825 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.35 ALA-H | 102826 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.35 ALA-H | 102827 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.35 ALA-H | 102831 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises |