RAG using Llama3, Langchain and ChromaDB
-
Updated
May 1, 2024 - Jupyter Notebook
RAG using Llama3, Langchain and ChromaDB
RAG-nificent is a state-of-the-art framework leveraging Retrieval-Augmented Generation (RAG) to provide instant answers and references from a curated directory of PDFs containing information on any given topic. Supports Llama3 and OpenAI Models via the Groq API.
META LLAMA3 GENAI Real World UseCases End To End Implementation Guide
Local RAG using LLaMA3
Experiment using Meta's newly released llama 3 model.
Add a description, image, and links to the llama3-rag topic page so that developers can more easily learn about it.
To associate your repository with the llama3-rag topic, visit your repo's landing page and select "manage topics."