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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

Product type Paperback

Published in Jan 2021

Publisher Packt

ISBN-13 9781800565791

Length 384 pages

Edition 1st Edition

Languages

Processing

Tools

BERT

Concepts

Mobile Application Development

Author (1):

Denis Rothman

View More author details

Table of Contents (16) Chapters

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

Getting started: Sentiment analysis transformers

In this section, we will first explore the SST that the transformers will use to train models on sentiment analysis.

We will then use AllenNLP to run a RoBERTa-large transformer.

The rest of the chapter is locked

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Authors (1)

Denis Rothman

Denis Rothman

Expert in AI Transformers including ChatGPT/GPT-4, Bestselling Author

See other products by Denis Rothman

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