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Extractive Question Answering using Hugging Face Transformers

Overview

This project implements an Extractive Question Answering (QA) system using Hugging Face Transformers. The goal is to accurately extract relevant information from text data in response to user queries. The project showcases proficiency in natural language processing and machine learning, leveraging cutting-edge models from Hugging Face Transformers.

Features

  • Utilizes state-of-the-art language models for accurate question answering.
  • Demonstrates advanced natural language processing techniques.
  • Provides a practical implementation for real-world applications.

Getting Started

Prerequisites

  • Python 3.x
  • Install dependencies: pip install -r requirements.txt

Usage

  1. Clone the repository: git clone https://github.com/your-username/extractive-qa-transformers.git
  2. Navigate to the project directory: cd extractive-qa-transformers
  3. Run the QA system: python main.py

About

This project implements an Extractive Question Answering (QA) system using Hugging Face Transformers.

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