Text Summarization using DistilBART

Overview

This project is an AI-powered text summarization application built using Hugging Face Transformers, the DistilBART model, and Gradio. It generates concise summaries from long text while preserving the key information.

Features

• Automatic text summarization
• DistilBART pre-trained model
• Interactive Gradio web interface
• Local inference using PyTorch
• Easy deployment to cloud platforms

Tech Stack

• Python 3.10
• PyTorch
• Hugging Face Transformers
• Gradio

Project Structure

Text-Summarization/
│
├── app.py
├── requirements.txt
├── README.md
├── LICENSE
└── .gitignore

Installation

git clone https://github.com/Sateeshkumar4425/Text-Summarization.git
cd Text-Summarization

python -m venv .venv
.\.venv\Scripts\activate

pip install -r requirements.txt

Run the Application

python app.py

The application will be available at:

http://127.0.0.1:7860

Model

This project uses the following Hugging Face model:

• sshleifer/distilbart-cnn-12-6

The model will be downloaded automatically during the first execution if it is not already available locally.

Application Preview

Home Screen

Input Example

Generated Summary

Future Improvements

• PDF summarization
• URL summarization
• Batch document summarization
• Model selection
• Deployment on Render

Author

Sateesh Kumar Patlegar

Gmail: patlegarsateeshkumar@gmail.com
LinkedIn: https://www.linkedin.com/in/patlegar-sateesh-kumar-868870258/
GitHub: https://github.com/Sateeshkumar4425

Open to Data Science, Analytics, Machine Learning, and Quantitative Research opportunities.