---
title: Emotion Detection App
emoji: 😊
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: "4.27.0"
app_file: app.py
pinned: false
---

# 😊 Emotion Detection from Text using BERT

Welcome to the **Emotion Detection Web App**! This application uses a fine-tuned BERT model to detect human emotions from short pieces of text.

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## 🚀 Demo

👉 Try the live app: [Click here to open the web app](https://huggingface.co/spaces/sujith13082003/emotion_detection)

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## 🔍 Description

This project leverages the `nateraw/bert-base-uncased-emotion` model from Hugging Face Transformers to classify input text into one of six emotions:

- 😢 Sadness
- 😀 Joy
- 💖 Love
- 😡 Anger
- 😱 Fear
- 😲 Surprise

It uses:
- **Hugging Face Transformers** for model and tokenizer
- **PyTorch** for deep learning inference
- **Gradio** to build an interactive web interface

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## 🧠 Model Used

- **Model Name**: `nateraw/bert-base-uncased-emotion`
- **Base Architecture**: BERT (uncased)
- **Dataset**: GoEmotions subset

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## 📦 Dependencies

Dependencies are defined in `requirements.txt`:
- `transformers`
- `torch`
- `gradio`

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## 📈 Use Cases

- Social media sentiment analysis
- Customer feedback classification
- Chatbot emotion understanding
- Mental health applications

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## 👨‍💻 Author

- **Sujith Kumar**
- Hugging Face: [@sujith13082003](https://huggingface.co/sujith13082003)

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## 📝 License

This project is for educational and research purposes. Refer to individual library licenses for commercial use.