# To save the model:
from keras.models import save_model
# you can write whatever you desire instead of 'my_model'
# model = Your trained model
model.save('my_model')
# To load the model:
from keras.models import load_model
reconstructed_model = load_model("my_model")
keras_model_path = "/tmp/keras_save"
model.save(keras_model_path)
restored_keras_model = tf.keras.models.load_model(keras_model_path)