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

pip install -r requirements.txt

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

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
README.md		README.md
Raport z projektu Retriever-Augmented Generation.pdf		Raport z projektu Retriever-Augmented Generation.pdf
finetune_embedding.ipynb		finetune_embedding.ipynb
gemma-generation-v2.ipynb		gemma-generation-v2.ipynb
llamaindex1(1).ipynb		llamaindex1(1).ipynb
medium.csv		medium.csv
questions.zip		questions.zip
requirements.txt		requirements.txt