Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Exploring GPT-3
  • Toc
  • feedback
Exploring GPT-3

Exploring GPT-3

By : Tingiris
4.3 (16)
close
Exploring GPT-3

Exploring GPT-3

4.3 (16)
By: Tingiris

Overview of this book

Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Whether you have a technical or non-technical background, this book will help you understand and start working with GPT-3 and the OpenAI API. If you want to get hands-on with leveraging artificial intelligence for natural language processing (NLP) tasks, this easy-to-follow book will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the book takes you through practical examples that show how to leverage the OpenAI API and GPT-3 for text generation, classification, and semantic search. You'll explore the capabilities of the OpenAI API and GPT-3 and find out which NLP use cases GPT-3 is best suited for. You’ll also learn how to use the API and optimize requests for the best possible results. With examples focusing on the OpenAI Playground and easy-to-follow JavaScript and Python code samples, the book illustrates the possible applications of GPT-3 in production. By the end of this book, you'll understand the best use cases for GPT-3 and how to integrate the OpenAI API in your applications for a wide array of NLP tasks.
Table of Contents (15 chapters)
close
1
Section 1: Understanding GPT-3 and the OpenAI API
4
Section 2: Getting Started with GPT-3
8
Section 3: Using the OpenAI API

Understanding general GPT-3 use cases

In the last chapter, you learned that the OpenAI API is a text in, text out interface. So, it always returns a text response (called a completion) to a text input (called a prompt). The completion might be generating new text, classifying text, or providing results for a semantic search. The general-purpose nature of GPT-3 means it could be used for almost any language processing task. To keep us focused, we're going to look at the following general use cases: text generation, classification, and semantic search:

  • Text generation: Text generation tasks are tasks for creating new, original text content. Examples include article writing and chatbots.
  • Classification: Classification tasks tag or classify text. Examples of classification tasks include things such as sentiment analysis and content filtering.
  • Semantic search: Semantic search tasks match a query with documents that are semantically related. For example, the query...
bookmark search playlist font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete