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.
- Implements RAG-based workflows for various tasks
- Integrates retrieval mechanisms with language models
- Provides examples and tutorials for learning and experimentation
Clone the repository:
git clone https://github.com/Shawon00s/Retrieval-Augmented-Generation_RAG_Learning.git
Explore the code and documentation to understand RAG concepts and try out sample workflows.