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

About the Authors

Lewis Tunstall is a data scientist at Swisscom, focused on building machine learning powered applications in the domains of natural language processing and time series. A former theoretical physicist, he has over 10 years experience translating complex subject matter to lay audiences and has taught machine learning to university students at both the graduate and undergraduate levels.

Leandro von Werra is a data scientist at Swiss Mobiliar where he leads the company's natural language processing efforts to streamline and simplify processes for customers and employees. He has experience working across the whole machine learning stack, and is the creator of a popular Python library that combines Transformers with reinforcement learning. He also teaches data science and visualisation at the Bern University of Applied Sciences.

Thomas Wolf is Chief Science Officer and co-founder of HuggingFace. His team is on a mission to catalyze and democratize NLP research. Prior to HuggingFace, Thomas gained a Ph.D. in physics, and later a law degree. He worked as a physics researcher and a European Patent Attorney.

"About this title" may belong to another edition of this title.

Store Description

Visit Seller's Storefront

Seller's business information

Swan Trading Company
TX, U.S.A.

Sale & Shipping Terms

Terms of Sale

We accept all Abebooks supported payment options displayed at checkout. Please contact us if you feel you need to return the book.

Swan Trading Company

Mark and Susan Lyons
2915 Brandy Ln
Georgetown, TX 78628
(512) 497-2398

Shipping Terms

We normally ship in one to two business days. If your book order is heavy or oversized, we may contact you to let you know extra shipping is required. We ship US Media Mail, Priority Mail, First Class International, and Priority Mail International.

Shipping rates within U.S.A.

Shipping rates within U.S.A.
Order quantity	5 to 14 business days	3 to 6 business days
First item	US$ 0.00	US$ 8.20

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.