🚀 Real-Time Text Sentiment Classifier with Gradio

A lightweight and powerful web app that classifies text as Positive or Negative using Hugging Face Transformers — built with Gradio and perfect for real-time use!

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🔍 About the Model

• Pipeline: text-classification
• Model: distilbert-base-uncased-finetuned-sst-2-english
• Task: Binary Sentiment Classification (Positive / Negative)
• Framework: Transformers by Hugging Face

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💡 App Features

• Real-time sentiment prediction from user text
• Lightweight, fast & responsive Gradio UI
• Deployed via Hugging Face Spaces — public & demo-ready

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📌 Instructions for Users

This app is trained for binary classification: Positive and Negative
Neutral or mixed inputs may lean toward one side.
For best results, use clearly positive or negative sentences.

✅ Example:

• "I love the performance of this app!" → Positive
• "Terrible experience, not recommended." → Negative

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🚀 Live Demo

👉 Try it here: Hugging Face Space Link

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📦 Requirements

Install all required packages:

pip install -r requirements.txt