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001450617 001__ 1450617
001450617 003__ OCoLC
001450617 005__ 20230310004535.0
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001450617 008__ 221025s2022\\\\nyua\\\\o\\\\\001\0\eng\d
001450617 019__ $$a1348866329
001450617 020__ $$a9781484288443$$q(electronic bk.)
001450617 020__ $$a1484288440$$q(electronic bk.)
001450617 020__ $$z9781484288436
001450617 020__ $$z1484288432
001450617 0247_ $$a10.1007/978-1-4842-8844-3$$2doi
001450617 035__ $$aSP(OCoLC)1348646387
001450617 040__ $$aORMDA$$beng$$erda$$epn$$cORMDA$$dGW5XE$$dEBLCP$$dYDX$$dOCLCF$$dUKAHL$$dOCLCQ
001450617 049__ $$aISEA
001450617 050_4 $$aQA76.9.N38
001450617 08204 $$a006.3/5$$223/eng/20221025
001450617 1001_ $$aJain, Shashank Mohan,$$eauthor.
001450617 24510 $$aIntroduction to transformers for NLP :$$bwith the Hugging Face library and models to solve problems /$$cShashank Mohan Jain.
001450617 2463_ $$aIntroduction to transformers for natural language processing
001450617 250__ $$a[First edition].
001450617 264_1 $$aNew York, NY :$$bApress,$$c2022.
001450617 300__ $$a1 online resource (169 pages) :$$billustrations
001450617 336__ $$atext$$btxt$$2rdacontent
001450617 337__ $$acomputer$$bc$$2rdamedia
001450617 338__ $$aonline resource$$bcr$$2rdacarrier
001450617 500__ $$aIncludes index.
001450617 5050_ $$aChapter 1: Introduction to Language Models -- Chapter 2: Introduction to Transformers -- Chapter 3: BERT -- Chapter 4: Hugging Face -- Chapter 5: Tasks Using the Huggingface Library -- Chapter 6: Fine-Tuning Pre-Trained Models -- Appendix A: Vision Transformers.
001450617 506__ $$aAccess limited to authorized users.
001450617 520__ $$aGet a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing. This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation. After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library.
001450617 650_0 $$aNatural language processing (Computer science)
001450617 655_0 $$aElectronic books.
001450617 77608 $$iPrint version: $$z1484288432$$z9781484288436$$w(OCoLC)1342491545
001450617 852__ $$bebk
001450617 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-1-4842-8844-3$$zOnline Access$$91397441.1
001450617 909CO $$ooai:library.usi.edu:1450617$$pGLOBAL_SET
001450617 980__ $$aBIB
001450617 980__ $$aEBOOK
001450617 982__ $$aEbook
001450617 983__ $$aOnline
001450617 994__ $$a92$$bISE