Large Language Model Tutorials(LLM Tutorials) Repository

Welcome to the Large Language Model Tutorials Repository! This repository is a collection of Jupyter notebooks designed to help you understand and work with large language models, such as GPT-3.5. It will also include tutorials of open-source models. Whether you're a developer, researcher, or just curious about these powerful language models, you'll find resources here to guide you through various tasks and applications.

Table of Contents

1. Getting Started
2. Tutorials
3. Contributing

Getting Started

To get started with this repository, follow these steps:

1. Clone the repository to your local machine:

git clone https://github.com/your-username/llm_tutorials.git

2. Make sure you have Jupyter Notebook installed on your system. If not, you can install it using pip:

pip install jupyter

3. Navigate to the repository folder:

cd llm_tutorials

4. Launch Jupyter Notebook:

jupyter notebook

5. Browse notebooks in notebooks folderand run the Jupyter notebooks to explore various topics related to large language models.
6. You can also run this notebooks in google colab.

Tutorials

In this repository, you'll find a variety of Jupyter notebooks covering the following topics:

• Introduction to Large Language Models
• Text Generation with GPT-3.5
• Fine-Tuning GPT-3.5 for Custom Tasks
• Text Summarization with GPT-3.5
• Sentiment Analysis with GPT-3.5
• Chatbot Development with GPT-3.5
• Language Translation with GPT-3.5
• Ethics and Considerations in Working with Large Language Models
• AI Safety with Large Lanuage Models
• AI Conciousness with LLMs

Feel free to explore, learn, and experiment with these tutorials. We encourage you to use the notebooks as a foundation for your own projects and research.

Contributing

We welcome contributions to this repository! If you have created your own tutorials, improved existing ones, or want to fix issues, please consider contributing. Here's how you can do that:

1. Fork the repository to your GitHub account.
2. Create a new branch with a descriptive name for your feature or fix.
3. Make your changes and commit them.
4. Submit a pull request with a clear description of your contributions.

Your contributions can help make this repository an even more valuable resource for the community.

Happy Coding!