Published July 28, 2025
| Version 0.1a
Demonstration of PDF Summarization
Description
The Jupyter notebook has been designed to provide a stepwise description for summarizing scientific PDFs using Natural Language Processing (NLP) techniques. It extracts text from uploaded PDFs and generates concise summaries using transformer-based models.
Features
- Upload and parse PDF documents
- Extract meaningful text content
- Generate summaries using Hugging Face Transformers (e.g., BART, T5)
- Optionally view original and summarized text side-by-side
- Includes visualization support with PyMuPDF and IPython.display
The notebbk can be used for the following applications
- Research paper summarization
- Literature review automation
- Information extraction for large documents
Files
RevLit_PDF_Summarization.ipynb
Files
(86.8 kB)
| Name | Size | Download all |
|---|---|---|
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md5:aa9be2ea736258f8d5f3c745ed0068ec
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86.8 kB | Preview Download |
Additional details
Dates
- Created
-
2025-07-28
Software
- Repository URL
- https://github.com/semanticClimate/PDF_Summarization_demo