Text_summarizer

This project implements a text summarization system using state-of-the-art natural language processing techniques.

Features

• Automatic text summarization
• Fine-tuning of pre-trained language models
• Evaluation metrics for summarization quality
• Support for both extractive and abstractive summarization

Technologies

• Python 3.x
• PyTorch
• Transformers library (Hugging Face)
• NLTK (Natural Language Toolkit)
• ROUGE (Recall-Oriented Understudy for Gisting Evaluation) for evaluation

Project Structure

• train.py: Main script for training the summarization model

Installation

1. Clone the repository:

   git clone https://github.com/your-username/Text_summarizer.git
   cd Text_summarizer
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

1. Prepare your dataset in the required format.

2. Run the training script:

   python train.py
   

3. For inference, use:

   python inference.py --input "Your text to summarize"
   

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0) - see the LICENSE file for details.