User-Question-Answering-Model

A machine learning-based question answering system using transformer models like BERT. Automatically answers questions from text passages with applications in education, customer support, and information retrieval.

📦 Features

• 📄 PDF text extraction using PyMuPDF (fitz)
• 🧠 BERT model (fine-tuned on SQuAD) for question answering
• ⚡ Fast answers with Hugging Face pipeline
• 🔧 Simple command-line interface

🚀 Deployment & Setup Guide

1. Clone the Repository:

   git clone https://github.com/yourusername/User-Question-Asnwering-Model.git

   cd User-Question-Asnwering-Model

2. Install Required Packages:

   pip install torch transformers PyMuPDF

   pip install -r requirements.txt

3. Code Editors:

   You can use any code editor, but it's recommended to use:

   • VS Code (Lightweight, Python support, integrated terminal)

   • PyCharm (Feature-rich IDE)

   Make sure to select the correct Python interpreter from your virtual environment.

4. Running the Program:

   Ensure your desired PDF file (e.g., sample_data.pdf) is in the same folder as user_qa.py

   Run the python code in terminal.