Isbn: 9781098136796 - natural language processing with transformers: building language applications with hugging face (15 Ergebnisse)

Paperback. Zustand: Very Good. 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.

Paperback. Zustand: Good. 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.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Paperback. Zustand: Brand New. revised edition. 406 pages. 9.19x7.00x0.84 inches. In Stock.

Zustand: New. In English.

Zustand: New. 2022. Revised. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. &Uumlber 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.

Zustand: NEW.

Taschenbuch. Zustand: 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. 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 answering - Learn how transformers can be used for cross-lingual transfer learning - Apply transformers in real-world scenarios where labeled data is scarce - Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization - Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments.…

paperback. Zustand: New.

Taschenbuch. Zustand: Neu. Natural Language Processing with Transformers | Lewis Tunstall (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | O'Reilly Media | EAN 9781098136796 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: 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. 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 answering - Learn how transformers can be used for cross-lingual transfer learning - Apply transformers in real-world scenarios where labeled data is scarce - Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization - Train transformers from scratch and learn how to scale to multiple GPUs and distributed environmentsLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.…

Taschenbuch. Zustand: 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. 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 answering - Learn how transformers can be used for cross-lingual transfer learning - Apply transformers in real-world scenarios where labeled data is scarce - Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization - Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments Englisch.…