You're reading from Transformers for Natural Language Processing Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781803247335

Length 602 pages

Edition 2nd Edition

Languages

Processing

Tools

Processing

Concepts

Mobile Application Development

Author (1):

Denis Rothman

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Table of Contents (25) Chapters

Preface

1. What are Transformers? FREE CHAPTER

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

Jump-starting the ChatGPT API

The original ChatGPT is a GPT-3.5 model that includes GPT-3.5-turbo. These models are an evolution of the GPT-3 model. You are just a step away from home. But what a step!

Open Jump_Starting_ChatGPT_with_the_OpenAI_API.ipynb.

Install and import OpenAI and enter the API key.

This is the same process applied in Chapter 7, The Rise of Suprahuman Transformers with GPT-3 Engines. Review this chapter if necessary.

Content generation

OpenAI has introduced an innovative request approach:

The request is formulated with a ChatCompletion call.
The model called is gpt-3.5-turbo, a powerful conversational AI better known to the public as ChatGPT.
Each object of a message has a role: system, assistant, and user. The system role can be a general message, the assistant can provide factual information for the model, and the user role contains the core of the request. Once our prompt is designed, we run it:
```
response=openai...
```

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You're reading from Transformers for Natural Language Processing Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4

Table of Contents (25) Chapters

Jump-starting the ChatGPT API

Content generation

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Authors (1)