loadmodel

#Save the model using pickle
import pickle
# save the model to disk
pickle.dump(model, open(model_file_path, 'wb'))

#Load the model 
model = pickle.load(open(model_file_path, 'rb'))

#Saving a Keras model
# Calling `save('my_model')` creates a SavedModel folder `my_model`.
model.save("my_model")
#Load a Keras Model
# It can be used to reconstruct the model identically.
reconstructed_model = keras.models.load_model("my_model")