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Mastering Transformers

You're reading from   Mastering Transformers Build state-of-the-art models from scratch with advanced natural language processing techniques

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801077651
Length 374 pages
Edition 1st Edition
Languages
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Authors (2):
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Savaş Yıldırım Savaş Yıldırım
Author Profile Icon Savaş Yıldırım
Savaş Yıldırım
Meysam Asgari- Chenaghlu Meysam Asgari- Chenaghlu
Author Profile Icon Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction – Recent Developments in the Field, Installations, and Hello World Applications
2. Chapter 1: From Bag-of-Words to the Transformer FREE CHAPTER 3. Chapter 2: A Hands-On Introduction to the Subject 4. Section 2: Transformer Models – From Autoencoding to Autoregressive Models
5. Chapter 3: Autoencoding Language Models 6. Chapter 4:Autoregressive and Other Language Models 7. Chapter 5: Fine-Tuning Language Models for Text Classification 8. Chapter 6: Fine-Tuning Language Models for Token Classification 9. Chapter 7: Text Representation 10. Section 3: Advanced Topics
11. Chapter 8: Working with Efficient Transformers 12. Chapter 9:Cross-Lingual and Multilingual Language Modeling 13. Chapter 10: Serving Transformer Models 14. Chapter 11: Attention Visualization and Experiment Tracking 15. Other Books You May Enjoy

Working with community-provided models

Hugging Face has tons of community models provided by collaborators from large Artificial Intelligence (AI) and Information Technology (IT) companies such as Google and Facebook. There are also many interesting models that individuals and universities provide. Accessing and using them is also very easy. To start, you should visit the Transformer models directory available at their website (https://huggingface.co/models), as shown in the following screenshot:

Figure 2.11 – Hugging Face models repository

Apart from these models, there are also many good and useful datasets available for NLP tasks. To start using some of these models, you can explore them by keyword searches, or just specify your major NLP task and pipeline.

For example, we are looking for a table QA model. After finding a model that we are interested in, a page such as the following one will be available from the Hugging Face website (https://huggingface...

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