---
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](https://huggingface.co/snehal1219901)  
As part of a hands-on learning series with Hugging Face 🤗