README.md

metadata

title: Text Summarizer App
emoji: ✂️
colorFrom: blue
colorTo: pink
sdk: gradio
sdk_version: 4.28.0
app_file: app.py
pinned: false

✂️ Text Summarization with Hugging Face Transformers

This is a beginner-friendly NLP project demonstrating how to perform text summarization using Hugging Face’s transformers pipeline. It uses a pretrained DistilBART model to condense long-form text into short, readable summaries.

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🚀 What This Space Does

• Uses the 🤗 pipeline() API for summarization
• Leverages the pretrained model: sshleifer/distilbart-cnn-12-6
• Takes a block of input text and returns a concise summary
• Built with Gradio for an interactive UI experience

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🧠 How to Use It

1. Enter a paragraph or article in the textbox
2. Click Submit to generate a summary
3. Try experimenting with different types of text (news, blog posts, etc.)
4. Use the summary output as a reference, abstract, or TL;DR

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💡 What You'll Learn

• How to use Hugging Face pipeline() for text summarization
• How summarization models work in NLP
• How to quickly turn Python code into a usable web app with Gradio

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📚 Model Details

• Model: sshleifer/distilbart-cnn-12-6
• Type: Abstractive summarization
• Base Architecture: DistilBART (a distilled version of Facebook’s BART model)

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🙌 Author

Built by Snehal Bandekar
As part of a hands-on learning series with Hugging Face 🤗