Natural Language Processing with Transformers: Building Language Applications with Hugging Face.

Natural Language Processing with Transformers: Building Language Applications with Hugging Face

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ISBN: 9781098103248 | 410 pages | 11 Mb

Natural Language Processing with Transformers: Building Language Applications with Hugging Face
Page: 410
Format: pdf, ePub, fb2, mobi
ISBN: 9781098103248
Publisher: O'Reilly Media, Incorporated

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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. 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

Explainable Natural Language Processing - Amazon.com
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Natural Language Processing: Books - Amazon.com
Natural Language Processing with Transformers: Building Language Applications with Hugging Face 39 30. $59.99 9 · Machine Learning with
How the revolution of natural language processing is
Clement Delangue is the co-founder and CEO of Hugging Face, a startup focused on natural language processing that has raised more than $20M. The company created
Amazon.com: Thomas Wolf - AI & Machine Learning
Natural Language Processing with Transformers: Building Language Applications with Hugging Face. by Lewis Tunstall , Leandro von Werra , et al.
Natural Language Processing with Hugging Face
The package provides pre-trained models that can be used for numerous NLP tasks. Transformers also supports over 100 languages. It also provides the ability to
Natural Language Processing with Transformers - Booktopia
Booktopia has Natural Language Processing with Transformers, Building Language Applications with Hugging Face by Lewis Tunstall.
Natural Language Processing with Transformers - Google Books
Natural Language Processing with Transformers: Building Language Applications with Hugging Face · Build, debug, and optimize transformer models for core NLP
Natural Language Processing with Transformers - Amazon.ca
Natural Language Processing with Transformers: Building Language Applications with Hugging Face: Tunstall, Lewis, Werra, Leandro Von, Wolf,
Explainable Natural Language Processing - Amazon.com
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Leandro von Werra on Twitter: "Our book "Natural Language
Our book "Natural Language Processing with Transformers: Building Language Applications with Hugging Face" can now be preordered!
Transformers - Hugging Face

Transformer (machine learning model) - Wikipedia
Like recurrent neural networks (RNNs), transformers are designed to handle sequential input data, such as natural language, for tasks such as translation and
Amazon.com: Lewis Tunstall - AI & Machine Learning
Natural Language Processing with Transformers: Building Language Applications with Hugging Face. by Lewis Tunstall , Leandro von Werra , et al.
Natural Language Processing with Transformers - Goodreads
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Natural Language Processing Specialization - Coursera
Offered by deeplearning.ai. Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the

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