000 02253cam a2200301 i 4500
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020 _a9789355420329
082 0 4 _a006.35
_223
100 1 _aTunstall, Lewis
_94277
245 1 0 _aNatural language processing with transformers :
_bbuilding language applications with Hugging Face /
_cLewis Tunstall, Leandro von Werra, and Thomas Wolf
260 _aMumbai :
_bO' reilly,
_c2022.
300 _axxii, 383p. ;
_bill. ,
504 _aIncludes bibliographical references and index.
505 0 _aHello transformers -- Text classification -- Transformer anatomy -- Multilingual named entity recognition -- Text generation -- Summarization -- Question answering -- Making transformers efficient in production -- Dealing with few to no labels -- Training transformers from scratch -- Future directions.
520 _aSince their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve.
650 0 _aNatural language processing (Computer science)
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650 0 _aElectronic transformers.
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650 2 _aNatural Language Processing
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650 6 _aTraitement automatique des langues naturelles.
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650 6 _aTransformateurs électroniques.
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650 7 _aElectronic transformers.
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650 7 _aNatural language processing (Computer science)
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650 7 _aNatural language processing (Computer science)
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650 7 _aElectronic transformers
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700 1 _aWerra, Leandro von,
_94280
700 1 _aWolf, Thomas,
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942 _2ddc
_cBK
999 _c752961
_d752961