Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Building AI Applications with ChatGPT APIs

You're reading from  Building AI Applications with ChatGPT APIs

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781805127567
Pages 258 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Martin Yanev Martin Yanev
Profile icon Martin Yanev

Table of Contents (19) Chapters

Preface 1. Part 1:Getting Started with OpenAI APIs
2. Chapter 1: Beginning with the ChatGPT API for NLP Tasks 3. Chapter 2: Building a ChatGPT Clone 4. Part 2: Building Web Applications with the ChatGPT API
5. Chapter 3: Creating and Deploying an AI Code Bug Fixing SaaS Application Using Flask 6. Chapter 4: Integrating the Code Bug Fixer Application with a Payment Service 7. Chapter 5: Quiz Generation App with ChatGPT and Django 8. Part 3: The ChatGPT, DALL-E, and Whisper APIs for Desktop Apps Development
9. Chapter 6: Language Translation Desktop App with the ChatGPT API and Microsoft Word 10. Chapter 7: Building an Outlook Email Reply Generator 11. Chapter 8: Essay Generation Tool with PyQt and the ChatGPT API 12. Chapter 9: Integrating ChatGPT and DALL-E API: Build End-to-End PowerPoint Presentation Generator 13. Chapter 10: Speech Recognition and Text-to-Speech with the Whisper API 14. Part 4:Advanced Concepts for Powering ChatGPT Apps
15. Chapter 11: Choosing the Right ChatGPT API Model 16. Chapter 12: Fine-Tuning ChatGPT to Create Unique API Models 17. Index 18. Other Books You May Enjoy

Fine-Tuning ChatGPT

In this section, you will learn about the process of fine-tuning ChatGPT models. We will talk about the ChatGPT models available for fine-tuning and provide information on their training and usage costs. We will also cover the installation of the openai library and set up the API key as an environmental variable in the terminal session. This section will serve as an overview of fine-tuning, its benefits, and the necessary setup to train a fine-tuned model.

Fine-tuning enhances the capabilities of API models in several ways. Firstly, it yields higher-quality outcomes compared to designing prompts alone. By incorporating more training examples than can be accommodated in a prompt, fine-tuning enables models to grasp a wider range of patterns and nuances. Secondly, it reduces token usage by utilizing shorter prompts, resulting in more efficient processing. Additionally, fine-tuning facilitates lower-latency requests, enabling faster and more responsive interactions...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}