python-kerasHow do I save a Keras model in Python?

Keras models can be saved in Python using the model.save() method. This method saves the architecture, weights, and training configuration of a model in a single HDF5 file.

Example code

from keras.models import load_model

model.save('model.h5')

This will create a single HDF5 file called model.h5 in the current working directory. The model can be reinstantiated at any time by calling the load_model() function with the path to the HDF5 file as an argument.

Example code

from keras.models import load_model

model = load_model('model.h5')

The load_model() function returns a compiled model identical to the original, including weights and training configuration.

Code explanation

1. model.save(): Saves the architecture, weights, and training configuration of a model in a single HDF5 file.
2. load_model(): Loads a compiled model including weights and training configuration.

Helpful links

• Keras Documentation: Save and serialize models

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