Description
Book Synopsis: 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. Read more
Details
Transformers have revolutionized the field of natural language processing, and now you have the opportunity to master this cutting-edge technology with the Natural Language Processing with Transformers, Revised Edition book. Written by the experts behind Hugging Face Transformers, this practical guide will take your data science and coding skills to the next level.
With the help of this book, you will learn how to train and scale large transformer models using the Python-based Hugging Face Transformers library. From writing realistic news stories to improving Google Search queries, transformers have already proven their capabilities in various NLP tasks. Now, it's time for you to harness these powerful models.
Authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf provide a hands-on approach to teach you the ins and outs of transformers. You'll discover how to integrate them into your applications and solve a wide range of tasks, including text classification, named entity recognition, and question answering.
What sets this book apart is its focus on real-world scenarios where labeled data is scarce. You'll learn how to apply transformers in situations where obtaining labeled data is challenging, thanks to techniques like cross-lingual transfer learning. Moreover, the authors share their expertise on making transformer models efficient for deployment, using methods like distillation, pruning, and quantization.
Whether you're a seasoned professional or just getting started with NLP, the Natural Language Processing with Transformers, Revised Edition book is a must-have resource. Gain a deep understanding of transformers, train models from scratch, and scale them to multiple GPUs and distributed environments with ease.
Don't miss out on the opportunity to become a master of transformers, the most advanced architecture for NLP. Order your copy of Natural Language Processing with Transformers, Revised Edition today and embark on a journey towards NLP excellence.
For more information and to purchase the book, click here.
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