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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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Toc

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

AR language model training

In this section, you will learn how it is possible to train your own AR language models. We will start with GPT-2 and get a deeper look inside its different functions for training, using the transformers library.

You can find any specific corpus to train your own GPT-2, but for this example, we used Emma by Jane Austen, which is a romantic novel. Training on a much bigger corpus is highly recommended to have a more general language generation.

Before we start, it's good to note that we used TensorFlow's native training functionality to show that all Hugging Face models can be directly trained on TensorFlow or PyTorch if you wish to. Follow these steps:

  1. You can download the Emma novel raw text by using the following command:
    wget https://raw.githubusercontent.com/teropa/nlp/master/resources/corpora/gutenberg/austen-emma.txt
  2. The first step is to train the BytePairEncoding tokenizer for GPT-2 on a corpus that you intend to train your...
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