This project demonstrates text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model. BART is a transformer model trained as a denoising autoencoder and is effective for text generation tasks such as summarization.
- Text Preprocessing: Load and preprocess text data.
- Summarization Model: A BART model for text summarization.
- Training Script: Train the model with text data.
- Summarization Script: Generate text summaries using the trained model.
- Results Visualization: Save and view generated summaries.
- Clone the repository and install dependencies:
git clone https://github.com/SreeEswaran/Text-Summarization-using-BART.git
cd Text-Summarization-using-BART-
Install the dependencies
pip install -r requirements.txt