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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

It's time to make a decision

What will a project manager's decision be? We have seen the limits of the original Transformer model, which leads to the crossroads where we have to choose a path to:

  • Accept the limits of the original Transformer model and move on to huge models requiring huge machine memory and computing power.
  • To refuse the limits of the original Transformer and tweak its architecture with reformer-type approaches.
  • Use different training methods such as PET, an efficient knowledge distillation approach.
  • Use a combination of these approaches.
  • Design your own training methods and model architecture.

    There are many transformer model methods continuously appearing on the market. Take the necessary time to find the right path for your project.

In real-life project management, each approach will be carefully evaluated using standard evaluation parameters:

  • The cost of each solution
  • ...
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