building language applications with Hugging Face Tunstall, Lewis creator Werra, Leandro von Wolf, Thomas text First edition. monographic xxii, 383 pages : illustrations ; 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. 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. Lewis Tunstall, Leandro von Werra, and Thomas Wolf ; Foreword by Aurélien Géron. Includes bibliographical references and index. 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 1098103246 9781098103248 9781098136796 1098136799 20250903113528.0