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tf.keras.models.save_model

Saves a model as a .keras file.

tf.keras.models.save_model(
    model, filepath, overwrite=True, **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.

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 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.

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model