Skip to content

Latest commit

 

History

History
10 lines (6 loc) · 367 Bytes

File metadata and controls

10 lines (6 loc) · 367 Bytes

-RAG-Powered-Document-Answering-System

Designed a Retrieval-Augmented Generation (RAG) system for document questionanswering

• Integrated Llama 3 7B model for language understanding

• Utilized LlamaIndex framework for efficient information retrieval

• Implemented Chroma DB for vector storage

• Generated embeddings using BAAI/bge-small-en-v1.5 model