keras_save_model.py

# Saving a model
network.save(filepath='./network.h5') # architecture + weights
network_json = network.to_json() # only the architecture
network.save_weights() # only the weights

# Restoring a saved model
new_network = keras.models.load_model('./another_model.h5')

# Using the ModelCheckpoint callback during training
callbacks = [
    callbacks.ModelCheckpoint('./model.h5', verbose=1, save_best_only=True),
    callbacks.EarlyStopping(monitor='val_loss', patience=2, verbose=1)
]

new_network.fit(train_images,
            train_labels,
            epochs=500,
            batch_size=128,
            validation_data=(val_images, val_labels),
            callbacks=callbacks)