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nf4

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This project implements a classic Retrieval-Augmented Generation (RAG) system using HuggingFace models with quantization techniques. The system processes PDF documents, extracts their content, and enables interactive question-answering through a Streamlit web application.

  • Updated Jul 18, 2025
  • Python

This project presents a medical question–answering language model built by fine-tuning Google Gemma-2-2B-IT using LoRA (Low-Rank Adaptation) 🧠⚕️. The primary objective is to adapt a general-purpose large language model to the healthcare domain in a parameter-efficient, reproducible, and resource-aware manner.

  • Updated Dec 28, 2025
  • Jupyter Notebook

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