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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
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  • 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

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 Kindle Edition
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 
[PDF] HuggingFace's Transformers: State-of-the-art Natural
HuggingFace's Transformers: State-of-the-art Natural Language Processing · Figures and Topics from this paper · 2,358 Citations · References.
Natural Language Processing with Transformers Book
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 
Build innovative deep neural network architectures for NLP
Transformers for Natural Language Processing: Build innovative deep neural network Facebook, Microsoft, OpenAI, and Hugging Face.
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 
Explainable Natural Language Processing - Amazon.com
Page 1 of 7 Start overPage 1 of 7. Previous page. Natural Language Processing with Transformers: Building Language Applications with Hugging Face.
Natural Language Processing with Transformers - Goodreads
If you're a data scientist or machine learning engineer, this practical book shows you how to train and scale these large models using HuggingFace Transformers, 
Natural Language Processing with Transformers : Lewis Tunstall
Natural Language Processing with Transformers : Building Language Applications with Hugging Face Available. Expected delivery to the United 
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 
Transformers for Natural Language Processing - Amazon.com
It expertly introduces transformers and mentors the reader for building innovative deep neural network architectures for NLP. The book covers almost all game- 
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.

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