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Transformers for Natural Language Processing

You're reading from   Transformers for Natural Language Processing Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781800565791
Length 384 pages
Edition 1st Edition
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with the Model Architecture of the Transformer 2. Fine-Tuning BERT Models FREE CHAPTER 3. Pretraining a RoBERTa Model from Scratch 4. Downstream NLP Tasks with Transformers 5. Machine Translation with the Transformer 6. Text Generation with OpenAI GPT-2 and GPT-3 Models 7. Applying Transformers to Legal and Financial Documents for AI Text Summarization 8. Matching Tokenizers and Datasets 9. Semantic Role Labeling with BERT-Based Transformers 10. Let Your Data Do the Talking: Story, Questions, and Answers 11. Detecting Customer Emotions to Make Predictions 12. Analyzing Fake News with Transformers 13. Other Books You May Enjoy
14. Index
Appendix: Answers to the Questions

Text completion with GPT-2

This section will clone the OpenAI GPT-2 repository, download the 345M parameter GPT-2 transformer model, and interact with it. We will enter context sentences and analyze the text generated by the transformer. The goal is to see how it creates new content.

This section is divided into 9 steps. Open OpenAI_GPT_2.ipynb in Google Colaboratory. The notebook is in the chapter of the GitHub repository of this book. You will notice that the notebook is also divided into the same 9 steps and cells as this section.

Run the notebook cell by cell. The process is tedious, but the result produced by the cloned OpenAI GPT-2 repository is gratifying.

It is important to note that we are running a low-level GPT-2 model and not a one-line call to obtain a result. We are also avoiding pre-packaged versions. We are getting our hands dirty to understand the architecture of a GPT-2 from scratch. You might get some deprecation messages. However, the effort...

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