You're reading from Transformers for Natural Language Processing - Second Edition

Product type Book

Published in Mar 2022

Publisher Packt

ISBN-13 9781803247335

Pages 602 pages

Edition 2nd Edition

Languages

Concepts

Mobile Application Development

Author (1):

Denis Rothman

Table of Contents (25) Chapters

Preface

1. What are Transformers?

2. Getting Started with the Architecture of the Transformer Model

3. Fine-Tuning BERT Models

4. Pretraining a RoBERTa Model from Scratch

5. Downstream NLP Tasks with Transformers

6. Machine Translation with the Transformer

7. The Rise of Suprahuman Transformers with GPT-3 Engines

8. Applying Transformers to Legal and Financial Documents for AI Text Summarization

9. Matching Tokenizers and Datasets

10. Semantic Role Labeling with BERT-Based Transformers

11. Let Your Data Do the Talking: Story, Questions, and Answers

12. Detecting Customer Emotions to Make Predictions

13. Analyzing Fake News with Transformers

14. Interpreting Black Box Transformer Models

15. From NLP to Task-Agnostic Transformer Models

16. The Emergence of Transformer-Driven Copilots

17. The Consolidation of Suprahuman Transformers with OpenAI’s ChatGPT and GPT-4

18. Other Books You May Enjoy

19. Index

Appendix I — Terminology of Transformer Models

1. Appendix II — Hardware Constraints for Transformer Models

2. Appendix III — Generic Text Completion with GPT-2

3. Appendix IV — Custom Text Completion with GPT-2

4. Appendix V — Answers to the Questions

Standard NLP tasks with specific vocabulary

This section focuses on Case 4: Rare words and Case 5: Replacing rare words from the Word2Vec tokenization section of this chapter.

We will use Training_OpenAI_GPT_2_CH09.ipynb, a renamed version of the notebook we used to train a dataset in Chapter 7, The Rise of Suprahuman Transformers with GPT-3 Engines.

Two changes were made to the notebook:

dset, the dataset, was renamed mdset and contains medical content
A Python function was added to control the text that was tokenized using byte-level BPE

We will not describe Training_OpenAI_GPT_2_CH09.ipynb, which we covered in Chapter 7, The Rise of Suprahuman Transformers with GPT-3 Engines, and Appendices III and IV. Make sure you upload the necessary files before beginning, as explained in Chapter 7.

There is no limit to the time you wish to train the model for. Interrupt it in order to save the model.

The files are on GitHub in the gpt-2-train_files...