Natural language processing with transformers : building language applications with Hugging Face /
Tunstall, Lewis,
Natural language processing with transformers : building language applications with Hugging Face / Lewis Tunstall, Leandro von Werra, and Thomas Wolf ; Foreword by Aurélien Géron. - First edition. - xxii, 383 pages : illustrations ;
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.
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.
1098103246 9781098103248 9781098136796 1098136799
Natural language processing (Computer science)
Electronic transformers.
Natural Language Processing
Traitement automatique des langues naturelles.
Transformateurs électroniques.
Electronic transformers.
Natural language processing (Computer science)
Natural language processing (Computer science)
Electronic transformers
006.35 / TUN
Natural language processing with transformers : building language applications with Hugging Face / Lewis Tunstall, Leandro von Werra, and Thomas Wolf ; Foreword by Aurélien Géron. - First edition. - xxii, 383 pages : illustrations ;
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.
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.
1098103246 9781098103248 9781098136796 1098136799
Natural language processing (Computer science)
Electronic transformers.
Natural Language Processing
Traitement automatique des langues naturelles.
Transformateurs électroniques.
Electronic transformers.
Natural language processing (Computer science)
Natural language processing (Computer science)
Electronic transformers
006.35 / TUN