Retrieval-Augmented Generation (RAG) Learning

This repository contains resources and code for exploring Retrieval-Augmented Generation (RAG) models. RAG is an approach that combines retrieval of relevant information from external sources with generative models to produce more accurate and context-aware outputs.

Key Features

• Implements RAG-based workflows for various tasks
• Integrates retrieval mechanisms with language models
• Provides examples and tutorials for learning and experimentation

Getting Started

Clone the repository:

git clone https://github.com/Shawon00s/Retrieval-Augmented-Generation_RAG_Learning.git

Usage

Explore the code and documentation to understand RAG concepts and try out sample workflows.

Author

• Shawon00s