Text Summarization with Fine-tuned Pegasus Model

In this project, I implemented a text summarization application using a fine-tuned Google/Pegasus model, trained on the CNN/DailyMail dataset. The model utilizes advanced transformer architecture to generate accurate and concise summaries from lengthy text. By inputting text, users can quickly receive a clear, readable summary generated by the model.

The application is built with Gradio, providing a smooth, user-friendly interface for summarization tasks. This project demonstrates the effectiveness of transformer-based models in tackling complex natural language processing tasks such as summarization.

You can try the app here.