Create README.md

README.md

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+---
+title: MNIST Digit Recognition
+emoji: 🎯
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.0.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# 🎯 MNIST Digit Recognition Demo
+
+Draw a digit (0-9) and watch the AI recognize it with **99.6% accuracy**!
+
+## About This Model
+
+This Space demonstrates a Convolutional Neural Network trained on the MNIST dataset, achieving exceptional performance:
+
+- **Test Accuracy:** 99.60%
+- **Model Size:** 271K parameters
+- **Architecture:** 4-layer CNN with batch normalization
+- **Framework:** PyTorch
+
+## How to Use
+
+1. **Draw a digit** in the canvas on the left
+2. **Wait a moment** for the prediction
+3. **See the result** with confidence scores for all digits
+
+The model was trained using advanced techniques including:
+- Data augmentation (rotation, scaling, random erasing)
+- OneCycleLR scheduler with warmup
+- Dropout and batch normalization
+- Early stopping
+
+## Model Repository
+
+Full training code and model weights: [mnist-cnn-classifier](https://huggingface.co/developerPratik/mnist-cnn-classifier)
+
+## Performance
+
+The model achieves near-perfect accuracy across all digits:
+- Most digits: 99-100% accuracy
+- Balanced performance (no digit is significantly harder)
+- Fast inference (~5ms per image on CPU)
+
+Try it out and see if you can draw digits the model gets wrong! 🎨