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]

nivashuggingface/digit-recognition

Digit Recognition Model

Model Description

Training

Usage

nivashuggingface/
digit-recognition