---
language: en
license: mit
tags:
- tensorflow
- image-classification
- mnist
- digits
datasets:
- mnist
metrics:
- accuracy
---

# Digit Recognition Model

This model is trained to recognize handwritten digits from the MNIST dataset.

## Model Description

- **Model Type:** CNN with Attention
- **Task:** Image Classification
- **Input:** 28x28 grayscale images
- **Output:** Digit classification (0-9)

## Training

The model was trained on the MNIST dataset using a CNN architecture with attention mechanisms.

## Usage

```python
import tensorflow as tf
import numpy as np

# Load the model
model = tf.saved_model.load("path_to_saved_model")

# Prepare input
image = tf.keras.preprocessing.image.load_img("digit.png", target_size=(28, 28))
image = tf.keras.preprocessing.image.img_to_array(image)
image = image.astype('float32') / 255.0
image = np.expand_dims(image, axis=0)

# Make prediction
predictions = model(image)
predicted_digit = tf.argmax(predictions, axis=1).numpy()[0]
```