Update README.md

README.md

@@ -10,4 +10,54 @@ pinned: false
 short_description: A dog loving space
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🐶 Dog Breed Classifier (Gradio + Hugging Face)
+
+This web app uses a powerful transformer-based model from Hugging Face to classify dog breeds from uploaded images.
+
+## 🔍 Model
+- **Name:** prithivMLmods/Dog-Breed-120
+- **Base architecture:** SigLIP (Vision Transformer)
+- **Classes:** 120 dog breeds
+
+## 🚀 Features
+- Built with **Gradio** for easy web interaction
+- Powered by **Transformers + PyTorch**
+- Can run on **Hugging Face Spaces** with no backend setup
+
+## 📁 File Structure
+```
+dog-breed-app/
+├── app.py             # Main app file
+├── requirements.txt   # Python dependencies
+└── README.md          # This file
+```
+
+## 🧪 Local Setup
+```bash
+# Create and activate environment (optional)
+conda create -n dog-breed python=3.10 -y
+conda activate dog-breed
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Run the app
+python app.py
+```
+
+## 🌐 Deploy to Hugging Face Spaces
+1. Go to [https://huggingface.co/spaces](https://huggingface.co/spaces)
+2. Create a new Space (select **Gradio** as SDK)
+3. Upload `app.py` and `requirements.txt`
+4. Your app will be live at: `https://huggingface.co/spaces/your-username/your-app`
+
+## ✨ Example Use
+Upload a photo like this:
+![example](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/spaces/dog-example.jpg)
+
+And get a result like:
+```
+golden_retriever (98.4%)
+```
+
+Enjoy building! 🐾