metadata
datasets:
- chromadb/paul_graham_essay
language:
- en
tags:
- RAG
- Retrieval Augmented Generation
- llama-index
Summary:
Retrieval Augmented Generation (RAG) is a technique to specialize a language model with a specific knowledge domain by feeding in relevant data so that it can give better answers.
Implemeting RAG(in a nutshell):
1. Ready/ Preprocess your input data:
Language Models see all the data as tokens and vectors. So we want to convert the data to be fed into the same format.