Skip to content

A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for AIGC applications.

License

Notifications You must be signed in to change notification settings

codenamerole/openai-quickstart

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 

Repository files navigation

OpenAI Quickstart

This project is designed as a one-stop learning resource for anyone interested in large language models and their application in Artificial Intelligence Governance and Control (AIGC) scenarios. By providing theoretical foundations, development basics, and hands-on examples, this project offers comprehensive guidance on these cutting-edge topics.

Features

  • Theory and Development Basics of Large Language Models: Deep dive into the inner workings of large language models like GPT-4, including their architecture, training methods, applications, and more.

  • AIGC Application Development with LangChain: Hands-on examples and tutorials using LangChain to develop AIGC applications, demonstrating the practical application of large language models.

Getting Started

You can start by cloning this repository to your local machine:

git clone https://github.com/DjangoPeng/openai-quickstart.git

Then navigate to the directory and follow the individual module instructions to get started.

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. If you have any suggestions or feature requests, please open an issue first to discuss what you would like to change.

License

This project is licensed under the terms of the MIT license. See the LICENSE file for details.

Contact

Django Peng - pjt73651@email.com

Project Link: https://github.com/DjangoPeng/openai-quickstart

About

A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for AIGC applications.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%