---
title: Zero Short Text Classification
emoji: 🐠
colorFrom: red
colorTo: blue
sdk: gradio
sdk_version: 5.34.1
app_file: app.py
pinned: false
license: mit
short_description: Zero-shot classification means no training data is needed.
---
# 🔍 Zero-Shot Text Classification with BART and XLM-RoBERTa

This Hugging Face Space is inspired by the article:  
🔗 [Zero-Shot Text Classification with BART and XLM-RoBERTa – C# Corner](https://www.c-sharpcorner.com/article/zero-shot-text-classification-with-bart-and-xlm-roberta/)

## 💡 What this app does:
- Takes any raw text input.
- Accepts user-defined labels (comma-separated).
- Uses Hugging Face's `pipeline("zero-shot-classification")` to predict the most relevant label(s) using:
  - **facebook/bart-large-mnli** or
  - **joeddav/xlm-roberta-large-xnli**

## 📦 Models Supported
- `facebook/bart-large-mnli` (English only)
- `joeddav/xlm-roberta-large-xnli` (Multilingual)

## ✅ Use Cases
- Categorizing feedback, support tickets, news headlines, etc.
- Works without any custom training — zero-shot!

## 🛠 How it Works
The model is prompted with your text and list of labels. It computes the probability of each label being appropriate, and returns scores.

---

Read the full article here:  
👉 [https://www.c-sharpcorner.com/article/zero-shot-text-classification-with-bart-and-xlm-roberta/](https://www.c-sharpcorner.com/article/zero-shot-text-classification-with-bart-and-xlm-roberta/)