This is a powerful and user-friendly web application for summarizing PDF files using advanced natural language processing techniques. It is built with Streamlit and integrates the LaMini-Flan-T5 language model for efficient and high-quality text summarization.
- PDF Uploading: Easily upload PDF files for processing.
- PDF Display: View the uploaded PDF within the app interface.
- Summarization: Generate concise and meaningful summaries of uploaded PDFs.
- Interactive Interface: A clean and responsive UI powered by Streamlit.
- Python: Core programming language.
- Streamlit: For creating the web interface.
- Transformers: Leveraging T5Tokenizer and T5ForConditionalGeneration.
- LangChain: For text splitting and preprocessing.
- PyTorch: For model inference.
- Python 3.8 or higher.
- Basic knowledge of Python virtual environments.
- Clone the repository:
git clone https://github.com/umair801/PDF_Summarization_App.git
This application uses the LaMini-Flan-T5-248M model for summarization. The model is available for free on Huggingface: https://huggingface.co/MBZUAI/LaMini-Flan-T5-248M. If it has not been downloaded, you can manually download it from the link above and place it in the model/LaMini-Flan-T5-248M directory within the project folder. The model does not require an API key to use.