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ISBN 10: 1098136799 ISBN 13: 9781098136796
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Paperback. Condition: new. Paperback. 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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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 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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ISBN 10: 1098136799 ISBN 13: 9781098136796
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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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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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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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Add to basketPaperback. Condition: new. Paperback. 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 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.