tf.keras.models.save_model

Saves a model as a .keras file.

tf.keras.models.save_model(
    model, filepath, overwrite=True, zipped=None, **kwargs
)

Used in the notebooks

Used in the tutorials
Train and serve a TensorFlow model with TensorFlow Serving

Args
model	Keras model instance to be saved.
filepath	str or pathlib.Path object. Path where to save the model.
overwrite	Whether we should overwrite any existing model at the target location, or instead ask the user via an interactive prompt.
zipped	Whether to save the model as a zipped .keras archive (default when saving locally), or as an unzipped directory (default when saving on the Hugging Face Hub).

Example:

model = keras.Sequential(
    [
        keras.layers.Dense(5, input_shape=(3,)),
        keras.layers.Softmax(),
    ],
)
model.save("model.keras")
loaded_model = keras.saving.load_model("model.keras")
x = keras.random.uniform((10, 3))
assert np.allclose(model.predict(x), loaded_model.predict(x))

Note that model.save() is an alias for keras.saving.save_model().

The saved .keras file is a zip archive that contains:

• The model's configuration (architecture)
• The model's weights
• The model's optimizer's state (if any)

Thus models can be reinstantiated in the exact same state.