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Exploring GPT-3

Exploring GPT-3

By : Tingiris
4.3 (16)
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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)
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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

Democratizing NLP

Anyone can use GPT-3 with access to the OpenAI API. The API is a general-purpose text in, text out interface that could be used for virtually any language task. To use the API, you simply pass in text and get a text response back. The task might be to do sentiment analysis, write an article, answer a question, or summarize a document. It doesn't matter, as far as the API is concerned—it's all done the same way, which makes using the API easy enough for just about anyone to use, even non-programmers.

The text you pass in is referred to as a prompt, and the returned text is called a completion. A prompt is used by GPT-3 to determine how best to complete the task. In the simplest case, a prompt can provide a few words to get started with. For example, if the prompt was If today is Monday, tomorrow is, GPT-3 would likely respond with Tuesday, along with some additional text such as If today is Tuesday, tomorrow is Wednesday, and so on. This means that what you get out of GPT-3 depends on what you send to it.

As you might guess, the quality of a completion depends heavily on the prompt. GPT-3 uses all of the text in a prompt to help generate the most relevant completion. Each and every word, along with how the prompt is structured, helps improve the language model prediction results. So, understanding how to write and test prompts is the key to unlocking GPT-3's true potential.

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