Text-Summarizer Using NLP

Text-Summarizer is a tool designed to generate summaries of text with customizable lengths. It leverages natural language processing (NLP) techniques to provide concise and coherent summaries based on user preferences.It also enables to find the synonyms and finding grammatical mistake using the BERT model.

Features

• Customizable Summary Length: Adjust the length of the generated summaries to meet your needs.
• Flexible Output Formats: Generate summaries in various formats suitable for different use cases.
• Natural Language Processing: Utilizes advanced NLP techniques for accurate and meaningful summaries.

Installation

1. Clone the repository:

   git clone https://github.com/rounakpaul11/Text-Summarizer.git

2. Navigate to the project directory:

   cd Text-Summarizer

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the application:

   python app.py

2. Provide text input and specify the desired summary length.

3. Receive the generated summary as output.

Configuration

Adjust the summary length and other parameters in the config.py file according to your needs.

Contributing

Contributions are welcome! Please open an issue or submit a pull request to contribute to the project.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or support, please contact tusharpanwar01872@gmail.com.