Natural Language Processing with Transformers: Building Language Applications with Hugging Face by
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- Natural Language Processing with Transformers: Building Language Applications with Hugging Face
- Page: 410
- Format: pdf, ePub, mobi, fb2
- ISBN: 9781098103248
- Publisher: O'Reilly Media, Incorporated
Download Natural Language Processing with Transformers: Building Language Applications with Hugging Face
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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
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
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.
Getting Started With Hugging Face Transformers for NLP
Hugging Face: The Best Natural Language Processing Ecosystem You're Not Using? If you've been even vaguely aware of developments in machine
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 : Lewis Tunstall
Natural Language Processing with Transformers : Building Language Applications with Hugging Face Available. Expected delivery to the United
Building Language Applications with Hugging Face Paperback
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Transformers for Natural Language Processing - Books
Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa,
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Natural Language Processing with Transformers - Amazon
Natural Language Processing with Transformers: Building Language Applications with Hugging Face : Tunstall,Lewis: Amazon.com.au: Books.
New Releases in Natural Language Processing - Amazon.com
Amazon Hot New ReleasesOur best-selling new and future releases. Updated hourly. New Releases in Natural Language Processing. #1. Natural Language
Natural Language Processing: NLP With Transformers in Python
Transformer models are the de-facto standard in modern NLP. They have proven themselves as the most expressive, powerful models for language by a large
Thomas Wolf
I'm interested in Natural Language Processing, Deep Learning and the work we do at Huggingface, current trends in AI/NLP and my unusual background.
Natural Language Processing with Hugging Face and
Hugging Face is a large open-source community that quickly became an enticing hub for pre-trained deep learning models, mainly aimed at NLP.
Transformer models - Hugging Face Course
Build, train and deploy state of the art models powered by the reference open Transformers is our natural language processing library and our hub is now
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