https://github.com/spectureram/text-summarization
A Python application that generates concise summaries of text using the BART model. With an interactive Streamlit interface, users can input text and choose from various summarization styles—Normal, Precise, or Accurate—to quickly obtain a tailored summary.
https://github.com/spectureram/text-summarization
bart huggingface machine-learning python
Last synced: 18 days ago
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A Python application that generates concise summaries of text using the BART model. With an interactive Streamlit interface, users can input text and choose from various summarization styles—Normal, Precise, or Accurate—to quickly obtain a tailored summary.
- Host: GitHub
- URL: https://github.com/spectureram/text-summarization
- Owner: SpectureRam
- License: mit
- Created: 2024-08-19T17:37:31.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-27T04:41:41.000Z (9 months ago)
- Last Synced: 2025-03-31T08:12:18.404Z (about 2 months ago)
- Topics: bart, huggingface, machine-learning, python
- Language: Python
- Homepage: https://huggingface.co/spaces/sairamn/text-summarization
- Size: 4.88 KB
- Stars: 7
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Text Summarization Tool
This project is a **Text Summarization Tool** built using the BART model (`facebook-bart-large-cnn`) and Streamlit for an interactive web interface. The tool allows users to input text and choose from three summarization styles: **Normal**, **Precise**, and **Accurate**. The tool generates concise summaries of the input text by adjusting length and other parameters based on the selected style.
## Features
- **Interactive Web Interface**: Built with Streamlit, providing an easy-to-use platform for text summarization.
- **Customizable Summarization Styles**: Select from Normal, Precise, and Accurate styles to tailor the summary to your needs.
- **Real-time Summarization**: Generates summaries quickly using the pre-trained BART model.
## How It Works
1. **Input Text**: Enter the text you want to summarize in the provided text area.
2. **Choose Style**: Select a summarization style from the dropdown menu: Normal, Precise, or Accurate.
3. **Generate Summary**: Click the "Summarize" button to generate a concise summary of your input text.
## Installation
Follow these steps to run the project locally:
1. **Clone the repository**:
```bash
git clone https://github.com/yourusername/text-summarization-tool.git
cd text-summarization-tool
```
2. **Install dependencies**:
```bash
pip install -r requirements.txt
```
3. **Run the application**:
```bash
streamlit run app.py
```
## Dependencies
- Python 3.7+
- Transformers (`transformers`)
- TensorFlow (`tensorflow`)
- Streamlit (`streamlit`)
## Example Usage
1. Run the application using `streamlit run app.py`.
2. Open your web browser and navigate to `http://localhost:8501`.
3. Enter your text, choose the summarization style, and click "Summarize" to see the result.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Contributing
Contributions are welcome! Please feel free to submit a pull request or open an issue for any suggestions or improvements.
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