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Exploring GPT-3

You're reading from   Exploring GPT-3 An unofficial first look at the general-purpose language processing API from OpenAI

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781800563193
Length 296 pages
Edition 1st Edition
Languages
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Author (1):
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Steve Tingiris Steve Tingiris
Author Profile Icon Steve Tingiris
Steve Tingiris
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Understanding GPT-3 and the OpenAI API
2. Chapter 1: Introducing GPT-3 and the OpenAI API FREE CHAPTER 3. Chapter 2: GPT-3 Applications and Use Cases 4. Section 2: Getting Started with GPT-3
5. Chapter 3: Working with the OpenAI Playground 6. Chapter 4: Working with the OpenAI API 7. Chapter 5: Calling the OpenAI API in Code 8. Section 3: Using the OpenAI API
9. Chapter 6: Content Filtering 10. Chapter 7: Generating and Transforming Text 11. Chapter 8: Classifying and Categorizing Text 12. Chapter 9: Building a GPT-3-Powered Question-Answering App 13. Chapter 10: Going Live with OpenAI-Powered Apps 14. Other Books You May Enjoy

Assigning an ESRB rating to text

In the last example, we provided sample data to help with our classification task. But GPT-3 is pre-trained with a huge dataset, meaning it can perform a surprising number of classification tasks without providing any example data. Let's take a look at another example using the completions endpoint. In this example, we'll look at classifying text with an Entertainment Software Rating Board (ESRB) rating.

In this example, we will use the completions endpoint to assign an ESRB rating to text without any example data.

Node.js/JavaScript example

To create the ESRB rating classifier example in Node.js/JavaScript, follow these steps:

  1. Log in to replit.com and open your exploring-gpt3-node REPL.
  2. Create a new file – chapter08/esrb-rating-classifier.js.
  3. Add the following code to the beginning of the esrb-rating-classifier.js file:
    const axios = require('axios');
    const apiKey = process...
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