Published by O'Reilly Media (edition 1), 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
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Published by O'Reilly Media (edition 1), 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Published by O'Reilly Media (edition 1), 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Published by O'Reilly Media 7/5/2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketPaperback or Softback. Condition: New. Natural Language Processing with Transformers, Revised Edition 1.43. Book.
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Add to basketPaperback. Condition: New. 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 -now revised in full color- 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.Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answeringLearn how transformers can be used for cross-lingual transfer learningApply transformers in real-world scenarios where labeled data is scarceMake transformer models efficient for deployment using techniques such as distillation, pruning, and quantizationTrain transformers from scratch and learn how to scale to multiple GPUs and distributed environments.
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Add to basketPaperback. Condition: New. 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 -now revised in full color- 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.Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answeringLearn how transformers can be used for cross-lingual transfer learningApply transformers in real-world scenarios where labeled data is scarceMake transformer models efficient for deployment using techniques such as distillation, pruning, and quantizationTrain transformers from scratch and learn how to scale to multiple GPUs and distributed environments.
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Published by Oreilly & Associates Inc, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware - 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 -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.
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Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -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 -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.
Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -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 -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. 383 pp. Englisch.
Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -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 -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. 383 pp. Englisch.
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Add to basketCondition: New. Über den AutorLewis Tunstall is a data scientist at Swisscom, focused on building machine learning powered applications in the domains of natural language processing and time series. A former theoretical physicist, he has over 10 ye.
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Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -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 -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 383 pp. Englisch.
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Add to basketPaperback. Condition: New. 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 -now revised in full color- 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.Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answeringLearn how transformers can be used for cross-lingual transfer learningApply transformers in real-world scenarios where labeled data is scarceMake transformer models efficient for deployment using techniques such as distillation, pruning, and quantizationTrain transformers from scratch and learn how to scale to multiple GPUs and distributed environments.
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Published by Oreilly & Associates Inc, 2022
ISBN 10: 1098103246 ISBN 13: 9781098103248
Language: English
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Published by Oreilly & Associates Inc, 2022
ISBN 10: 1098136799 ISBN 13: 9781098136796
Language: English
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