Natural Language Processing with Transformers:
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 usi...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media, Inc
2022
|
| Ausgabe: | 1st edition |
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 https://learning.oreilly.com/library/view/-/9781098103231/?ar |
| Zusammenfassung: | 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 HuggingFace 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 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 |
| Beschreibung: | Online resource; Title from title page (viewed March 25, 2022) |
| Beschreibung: | 1 online resource (409 pages) Illustrationen, Diagramme |
| Format: | Mode of access: World Wide Web |
| ISBN: | 9781098103217 |
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| author | Tunstall, Lewis von Werra, Leandro Wolf, Thomas |
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| spelling | Tunstall, Lewis Verfasser aut Natural Language Processing with Transformers Tunstall, Lewis 1st edition Sebastopol, CA O'Reilly Media, Inc 2022 1 online resource (409 pages) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Online resource; Title from title page (viewed March 25, 2022) 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 HuggingFace 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 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 Mode of access: World Wide Web Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Natürliche Sprache (DE-588)4041354-8 gnd rswk-swf Textverarbeitung (DE-588)4059667-9 gnd rswk-swf Sprachverarbeitung (DE-588)4116579-2 gnd rswk-swf Deep learning (DE-588)1135597375 gnd rswk-swf Electronic books ; local Electronic books Natürliche Sprache (DE-588)4041354-8 s Sprachverarbeitung (DE-588)4116579-2 s Textverarbeitung (DE-588)4059667-9 s Maschinelles Lernen (DE-588)4193754-5 s Deep learning (DE-588)1135597375 s DE-604 von Werra, Leandro Verfasser aut Wolf, Thomas Verfasser aut Erscheint auch als Druck-Ausgabe 978-1-0981-0324-8 X:ORHE https://learning.oreilly.com/library/view/-/9781098103231/?ar Aggregator |
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| title | Natural Language Processing with Transformers |
| title_auth | Natural Language Processing with Transformers |
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| title_full | Natural Language Processing with Transformers Tunstall, Lewis |
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