Update README.md

README.md

@@ -1,8 +1,27 @@
-Emotion Detection from Text using BERT
+---
+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.
+
+---
+
+## 🚀 Demo
+
+👉 Try the live app: [Click here to open the web app](https://huggingface.co/spaces/sujith13082003/emotion_detection)
 
-Welcome to the Emotion Detection Web App. This application uses a fine-tuned BERT model to detect human emotions from short pieces of text.
+---
 
-#Description
+## 🔍 Description
 
 This project leverages the `nateraw/bert-base-uncased-emotion` model from Hugging Face Transformers to classify input text into one of six emotions:
 
@@ -14,41 +33,39 @@ This project leverages the `nateraw/bert-base-uncased-emotion` model from Huggin
 - 😲 Surprise
 
 It uses:
--Hugging Face Transformers** for model and tokenizer
--PyTorch for deep learning inference
--Gradio to build an interactive web interface
-
-Model Used
+- **Hugging Face Transformers** for model and tokenizer
+- **PyTorch** for deep learning inference
+- **Gradio** to build an interactive web interface
 
-Model Name: `nateraw/bert-base-uncased-emotion`
-Base Architecture: BERT (uncased)
-Dataset: GoEmotions subset
-
- How It Works
+---
 
-1. You type a sentence like:
-   > "I just got a new job!"
+## 🧠 Model Used
 
-2. The model analyzes the text and returns the predicted emotion with confidence score.
+- **Model Name**: `nateraw/bert-base-uncased-emotion`
+- **Base Architecture**: BERT (uncased)
+- **Dataset**: GoEmotions subset
 
+---
 
-Dependencies
+## 📦 Dependencies
 
 Dependencies are defined in `requirements.txt`:
 - `transformers`
 - `torch`
 - `gradio`
 
+---
 
- Use Cases
+## 📈 Use Cases
 
 - Social media sentiment analysis
 - Customer feedback classification
 - Chatbot emotion understanding
 - Mental health applications
 
+---
 
-**Author
+## 👨‍💻 Author
 
 - **Sujith Kumar**
 - Hugging Face: [@sujith13082003](https://huggingface.co/sujith13082003)
@@ -58,4 +75,3 @@ Dependencies are defined in `requirements.txt`:
 ## 📝 License
 
 This project is for educational and research purposes. Refer to individual library licenses for commercial use.
-