PDFy is a project that aims to help people who need to read a lot of PDF documents, such as students, researchers, lawyers, etc. PDFy is a smart PDF summarizer that can extract the main points, keywords, and summaries from any PDF document, and present them in a concise and easy-to-read format.
PDFy was born out of the frustration of having to read hundreds of pages of PDF documents every day, and not having enough time to digest the information. PDFy uses natural language processing and machine learning techniques to analyze the content and structure of PDF documents, and generate summaries that capture the essence of the document. PDFy can also highlight the important sentences, keywords, and figures in the document, and provide a table of contents and a list of references.
- Developed a smart PDF summarizer using LLMa2 model, Google Colab and Python
- Leveraged large language models (LLMs) to generate concise and easy-to-read summaries from any PDF document
- Utilized Google Colab to access GPUs and TPUs for faster and cheaper computation
- Implemented natural language processing and machine learning techniques to analyze the content and structure of PDF documents
- Customized the output format, length, and level of detail of the summaries according to user preferences
- Visualized the summaries using graphs and charts to highlight the main points and keywords