A lightweight, AI-powered web application that generates concise and coherent summaries of academic texts, research papers, articles, and technical documentation. Built using Hugging Face Transformers and Gradio, this tool is designed to assist graduate students, researchers, and knowledge workers by simplifying the summarization process.
Problem Statement
As a graduate researcher, I must regularly read and summarize voluminous research papers and academic journals. This is a time-consuming and mentally exhausting process. This routine process acts as a hurdle to productivity, slowing down the rate of literature review and knowledge synthesis. To address this issue, I developed an AI-powered summarization tool that utilizes the latest natural language processing techniques to create concise summaries from lengthy academic documents. This tool will be helpful for students, scholars, and professionals by automatically summarizing, saving time, and enhancing comprehension.
🚀 Features
- 🧑🧬 Abstractive Summarization using
distilbart-cnn-12-6(Hugging Face) - ⚙️ Built with Gradio for an interactive, browser-based UI
- 💾 Supports local inference for offline use
- 💬 Simple and intuitive user experience
- 👨🎓 Designed specifically for students, researchers, and educators
🧠 Model Information
This app uses the sshleifer/distilbart-cnn-12-6 model from Hugging Face, which is a distilled version of Facebook’s BART model fine-tuned on the CNN/DailyMail dataset for summarization tasks.
User Interaction Flow
The video of user interaction flow shows how the user’s paste the content and summarize the content using the backend processing using Hugging Face (distilbart-cnn-12-6) model.
Lets Connect
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Abhijeet Solanki