RAG with Phi-3 Notebook

Overview

• RAG (Retrieval Augmented Generation) with Phi-3
• Data: 100 LLM Papers to explore
• Works in a single P100 or in dual-T4
• You don't need any token or key to use Phi-3! 😀

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Features

• Retrieval-Augmented Generation: Leverages a retrieval mechanism to fetch relevant information and augment the generation process.
• Phi-3 Integration: Incorporates the Phi-3 algorithm for improved context understanding and response accuracy.
• Notebook Interface: Provides an interactive Jupyter notebook environment for easy experimentation and development.

Installation

To set up the RAG with Phi-3 Notebook, follow these steps:

1. Clone the repository:

git clone https://github.com/Configure-X/RAG-with-Phi-3.git

2. Install dependencies:

pip install -r requirements.txt

Usage

To use the RAG with Phi-3 Notebook:

1. Launch the Jupyter notebook:

jupyter notebook rag_phi3.ipynb

2. Follow the instructions within the notebook to execute the cells and interact with the model.

Contributing

Contributions are welcome!

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgments

• Thanks to the creators of the RAG model and the Phi-3 algorithm for their innovative work in the field of NLP.
• Appreciation to all contributors who have helped improve this project.