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swastikmaiti / Intro-to-RAG-with-CODEGEMMA-7B

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LLM is a very powerful tool. It often performs more than required (hallucinations) and may tend to generate output in a pattern it finds best. We need RAG to harness the power of LLM in a controlled manner. In this work we implement a simple RAG system with Codegemma and an in-memory Vector Database.

docker docker-compose gradio rag vector-database sentence-transformers llm codegemma
  • Updated May 30, 2024
  • Jupyter Notebook

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