Text Summarization using python

By Aryan Singh

Text summarization project using transformers and GUI. User inputs text, selects sentences count, and gets concise summary output.

The text summarization project simplifies lengthy text by generating concise summaries. Users input the text they wish to summarize and can select the desired number of sentences in the summary. The system employs transformer models like T5, which have been trained on vast amounts of data, to understand language patterns and generate accurate.

The utilization of transformer models enables our system to comprehend the context, semantics, and relationships within the input text. This technology excels at handling natural language processing tasks, making it proficient in condensing large volumes of text into meaningful and informative summaries. By leveraging the transformer's capabilities, our project ensures that the generated summaries are both concise and relevant.

To provide a user-friendly experience, our project incorporates a graphical user interface (GUI). The GUI allows users to interact with the summarization system intuitively. Users can easily input text, set the desired summary length, and obtain the summarization output with a simple click. The GUI's intuitive design enhances accessibility and encourages broader adoption of our text summarization tool.

 

required installations:

pip install transformers --user
pip install sentencepiece