Skip to content

Latest commit

 

History

History
25 lines (17 loc) · 683 Bytes

README.md

File metadata and controls

25 lines (17 loc) · 683 Bytes

RAG with TinyLlama and BAAI retriever

Overview

Retrieval-Augmented Generation (RAG) in this repository is build with Llama Index framework. LLM used is a TinyLlama/TinyLlama-1.1B-Chat-v1.0. BAAI retriever is a BAAI/bge-small-en-v1.5 model

Installation

pip install -r requirements.txt

Requirements

  • Tensorflow == 2.15.0
  • Pytorch == 2.2.1+cu121
  • Python >= 3.9
  • Transformers >= 4.34.0

Usage

For llamaindex1(1).ipynb and finetune_embedding.ipynb I used Google Collab with GPU T4. Notebook gemma-generation-v2.ipynb was used on kaggle.