Update README.md

README.md

@@ -4,34 +4,127 @@ emoji: 📄➡️✂️
 colorFrom: green
 colorTo: purple
 sdk: gradio
-sdk_version: 4.41.0
+sdk_version: 5.31.0
 app_file: app.py
 pinned: false
 license: afl-3.0
 ---
 
-# Text Summarization App
+---
+title: Text Summarizer
+emoji: 📄➡️✂️
+colorFrom: green
+colorTo: purple
+sdk: gradio
+sdk_version: 5.31.0
+app_file: app.py
+pinned: false
+license: afl-3.0
+---
+
+# Text Summarization App 📄✂️
+
+A web-based text summarization tool that uses state-of-the-art NLP models to generate concise summaries from long-form text. Built with Gradio and deployed on Hugging Face Spaces.
+
+![Demo Screenshot](text-summarization-logo.png)
+
+## 🚀 Live Demo
+
+Try the app: [text-summarization](https://huggingface.co/spaces/ashish-soni08/Text-Summarizer)
+
+## ✨ Features
+
+- **Instant Summarization**: Generate concise summaries from lengthy text in seconds
+- **Clean Interface**: Intuitive web UI built with Gradio
+- **Pre-trained Model**: Uses DistilBART-CNN for high-quality summarization
+- **Responsive Design**: Works on desktop and mobile devices
+
+## 🛠️ Technology Stack
+
+- **Backend**: Python, Hugging Face Transformers
+- **Frontend**: Gradio
+- **Model**: [DistilBART-CNN-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6)
+- **Deployment**: Hugging Face Spaces
+
+## 🏃‍♂️ Quick Start
+
+### Prerequisites
+
+```bash
+Python 3.8+
+pip
+```
+
+### Installation
+
+1. Clone the repository:
+```bash
+git clone https://github.com/Ashish-Soni08/text-summarization-app.git
+cd text-summarization-app
+```
+
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the application:
+```bash
+python app.py
+```
+
+4. Open your browser and navigate to `http://localhost:7860`
+
+## 📋 Usage
+
+1. **Input Text**: Paste or type the text you want to summarize in the input box
+2. **Generate Summary**: Click the "Submit" button
+3. **View Results**: The summarized text will appear in the output section
+
+### Example
+
+**Input:**
+```
+Artificial Intelligence has been transforming industries across the globe...
+[Your example text here]
+```
+
+**Output:**
+```
+AI is rapidly growing and transforming healthcare, finance, and transportation through machine learning advances.
+```
+
+## 🧠 Model Information
+
+This app uses DistilBART-CNN-12-6 (sshleifer/distilbart-cnn-12-6), a distilled version of Facebook's BART model:
+
+- Architecture: 12-layer encoder, 6-layer decoder transformer
+- Parameters: ~306 million parameters
+- Training Data: CNN/Daily Mail dataset
+- Performance: Rouge-2: 21.26, Rouge-L: 30.59
+- Speed: ~1.24x faster than full BART-large while maintaining competitive quality
 
-This application provides a simple interface to summarize text using a pre-trained model from Hugging Face's Transformers library. The model used under the hood is `DISTILBART-12-6-CNN`, a distilled version of BART fine-tuned on the CNN/Daily Mail dataset.
+## 📁 Project Structure
 
-## Features
+```
+text-summarization-app/
+├── app.py                 # Main Gradio application
+├── requirements.txt       # Python dependencies
+├── README.md             # Project documentation
+```
 
-- **Text Summarization**: Generate concise summaries of input text.
-- **User-Friendly Interface**: Built using Gradio for an easy-to-use web interface.
+## 📄 License
 
-## Model
+This project is licensed under the AFL-3.0 License - see the [LICENSE](LICENSE) file for details.
 
-- **Model Used**: [DISTILBART-12-6-CNN](https://huggingface.co/sshleifer/distilbart-cnn-12-6)
-- **Framework**: Hugging Face Transformers
+## 🙏 Acknowledgments
 
-## Software Packages
+- [Hugging Face](https://huggingface.co/) for the Transformers library and model hosting
+- [Gradio](https://gradio.app/) for the web interface framework
+- Original BART paper authors for the foundational research
 
-- **Gradio**: Used to create the web interface.
-- **Transformers**: Used for model inference.
-- **Spaces**: Utilized for GPU acceleration during model execution.
+## 📞 Contact
 
-## How to Use
+Ashish Soni - [email protected]
 
-1. Enter the text you want to summarize in the provided textbox.
-2. Click "Submit" to generate a summary.
-3. The summarized text will be displayed in the output box.
+Project Link: [text-summarization](https://github.com/Ashish-Soni08/text-summarization-app)