Update README.md

README.md

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----
-title: ConfliBERT GUI v2
-emoji: ⚡
-colorFrom: red
-colorTo: green
-sdk: gradio
-sdk_version: 4.38.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ConfliBERT Demo Application
+
+A web-based interface for ConfliBERT, a BERT-based model specialized in conflict and political event analysis. This application provides multiple Natural Language Processing capabilities including Named Entity Recognition (NER), Text Classification, Multi-label Classification, and Question Answering.
+
+## Features
+
+- **Named Entity Recognition (NER)**
+  - Identifies and classifies named entities in text
+  - Entities include: Organizations, Persons, Locations, Quantities, Weapons, Nationalities, Temporal references, and more
+  - Color-coded visualization of entities in the web interface
+
+- **Text Classification**
+  - Binary classification for conflict-related content
+  - Determines if text is related to conflict, violence, or politics
+  - Provides confidence scores for classifications
+
+- **Multi-label Classification**
+  - Categorizes text into multiple event types
+  - Categories include: Armed Assault, Bombing or Explosion, Kidnapping, and Other
+  - Provides confidence scores for each category
+
+- **Question Answering**
+  - Extracts answers from provided context based on questions
+  - Specialized for conflict-related queries
+
+## Installation
+
+1. Clone the repository:
+```bash
+git clone https://github.com/yourusername/conflibert-demo.git
+cd conflibert-demo
+```
+
+2. Create and activate a virtual environment:
+```bash
+python -m venv env
+source env/bin/activate  # On Windows, use: env\Scripts\activate
+```
+
+3. Install required packages:
+```bash
+pip install -r requirements.txt
+```
+
+### Requirements
+
+- Python 3.8+
+- PyTorch
+- TensorFlow
+- Transformers
+- Gradio
+- Pandas
+
+## Usage
+
+### Running the Application
+
+1. Start the application:
+```bash
+python app.py
+```
+
+2. Open your web browser and navigate to:
+```
+http://localhost:7860
+```
+
+### Using Different Features
+
+#### Individual Text Analysis
+
+1. Select the desired task from the dropdown menu:
+   - Named Entity Recognition
+   - Text Classification
+   - Multilabel Classification
+   - Question Answering
+
+2. For standard tasks:
+   - Enter your text in the input box
+   - Click Submit
+
+3. For Question Answering:
+   - Enter the context in the context box
+   - Enter your question in the question box
+   - Click Submit
+
+#### Batch Processing with CSV
+
+1. Prepare a CSV file with a 'text' column containing your texts
+
+2. Select the desired task:
+   - NER
+   - Text Classification
+   - Multilabel Classification
+
+3. Upload your CSV file using the file upload component
+
+4. Click Submit to process the entire file
+
+5. Download the results CSV containing the original text and analysis results
+
+## Model Information
+
+ConfliBERT uses several specialized models:
+
+- **NER Model**: `eventdata-utd/conflibert-named-entity-recognition`
+- **Binary Classification**: `eventdata-utd/conflibert-binary-classification`
+- **Multi-label Classification**: `eventdata-utd/conflibert-satp-relevant-multilabel`
+- **Question Answering**: `salsarra/ConfliBERT-QA`
+
+## Output Formats
+
+### NER Output
+```
+EntityType: Entity1, Entity2 || EntityType2: Entity3 | Entity4
+```
+
+### Binary Classification Output
+```
+Class (Confidence%)
+```
+
+### Multi-label Classification Output
+```
+Class1 (Confidence%) | Class2 (Confidence%)
+```
+
+## Technical Details
+
+### File Structure
+```
+conflibert-demo/
+├── app.py              # Main application file
+├── requirements.txt    # Package dependencies
+└── README.md          # Documentation
+```
+
+### Key Components
+
+- **UI Components**: Built using Gradio
+- **Backend Processing**: PyTorch and TensorFlow
+- **Data Processing**: Pandas for CSV handling
+- **Model Integration**: Hugging Face Transformers
+
+## Contributing
+
+1. Fork the repository
+2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
+3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
+4. Push to the branch (`git push origin feature/AmazingFeature`)
+5. Open a Pull Request
+
+## Credits
+
+Developed by:
+- [Sultan Alsarra](https://www.linkedin.com/in/sultan-alsarra-phd-56977a63/)
+- [Shreyas Meher](http://shreyasmeher.com)
+
+## License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## Institutional Support
+
+- [UTD Event Data](https://eventdata.utdallas.edu/)
+- [University of Texas at Dallas](https://www.utdallas.edu/)
+
+## Citation
+
+If you use this tool in your research, please cite:
+
+```bibtex
+@software{conflibert2024,
+  title = {ConfliBERT: A BERT-based Model for Conflict and Political Event Analysis},
+  author = {Alsarra, Sultan and Meher, Shreyas},
+  year = {2024},
+  publisher = {UTD Event Data},
+  url = {https://eventdata.utdallas.edu/conflibert/}
+}
+```