TY  - BOOK
AU  - Tunstall,Lewis
AU  - Werra,Leandro von
AU  - Wolf,Thomas
TI  - Natural language processing with transformers: building language applications with Hugging Face 
SN  - 1098103246
U1  - 006.35 23
KW  - Natural language processing (Computer science)
KW  - Electronic transformers
KW  - Natural Language Processing
KW  - Traitement automatique des langues naturelles
KW  - Transformateurs électroniques
N1  - Includes bibliographical references and index; Hello 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
N2  - Since 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
ER  -