/retrieval_augmented_generation-rag-

Building an Applicant Tracking System (ATS) powered by RAG (Retrieval Augmented Generation) and Mistral-7b, a 7-billion parameter language model

Primary LanguageJupyter Notebook

RAG

  • RAG is an AI framework for retrieving facts from an external knowledge base to ground large language models (LLMs) on the most accurate, up-to-date information and to give users insight into LLMs' generative process.

ATS USING RAG

  • Filter most suitable application or resume using retrieval augemented generation leveraging mistral-7b.

  • Requirements

- !pip install -q transformers
- !CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install  llama-cpp-python --no-cache-dir # remove args to work in cpu
- !pip install -q llama-index
- !pip -q install sentence-transformers