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      • You can save a model with model.save() or keras.models.save_model() (which is equivalent). You can load it back with keras.models.load_model(). The recommended format is the "Keras v3" format, which uses the.keras extension. There are, however, two legacy formats that are available: the TensorFlow SavedModel format and the older Keras H5 format.
      www.tensorflow.org/guide/keras/serialization_and_saving

      Save, serialize, and export models | TensorFlow Core

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  3. www.tensorflow.org › tutorials › kerasSave and load models | TensorFlow Core

    Apr 3, 2024 · Save the entire model. Call tf.keras.Model.save to save a model's architecture, weights, and training configuration in a single model.keras zip archive. An entire model can be saved in three different file formats (the new .keras format and two legacy formats: SavedModel, and HDF5).

  4. stackoverflow.com › questions › 63986663Keras SavedModel vs Tensorflow SavedModel - Stack Overflow

    Sep 21, 2020 · I'm reading the documentation and source code of the TensorflowJS converter and it makes a clear distinction between Keras SavedModel and Tensorflow SavedModel. What are the differences between the formats and what is the cross-format support story?

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  6. www.kdnuggets.com › 2021 › 02Saving and loading models in TensorFlow - KDnuggets

    The simple way to save the model in TensorFlow is that we can use the built-in function of Tensorflow.Keras.models “Model saving & serialization APIs” that is the save_weights method. Let’s say we have a sequential model in TensorFlow.

  7. www.tensorflow.org › guide › kerasSave, serialize, and export models | TensorFlow Core

    Aug 5, 2023 · You can save a model with model.save() or keras.models.save_model() (which is equivalent). You can load it back with keras.models.load_model(). The recommended format is the "Keras v3" format, which uses the .keras extension. There are, however, two legacy formats that are available: the TensorFlow SavedModel format and the older Keras H5 format.

  8. colab.research.google.com › github › tensorflowSave and load Keras models - Google Colab

    Introduction. A Keras model consists of multiple components: The architecture, or configuration, which specifies what layers the model contain, and how they're connected. A set of weights...

  9. www.tensorflow.org › guide › saved_modelUsing the SavedModel format | TensorFlow Core

    Mar 23, 2024 · A SavedModel contains a complete TensorFlow program, including trained parameters (i.e, tf.Variable s) and computation. It does not require the original model building code to run, which makes it useful for sharing or deploying with TFLite, TensorFlow.js, TensorFlow Serving, or TensorFlow Hub.

  10. keras.io › 2 › apiWhole model saving & loading - Keras

    save_model function. tf_keras.saving.save_model( model, filepath, overwrite=True, save_format=None, **kwargs ) Saves a model as a TensorFlow SavedModel or HDF5 file. See the Serialization and Saving guide for details. Arguments. model: TF-Keras model instance to be saved. filepath: str or pathlib.Path object. Path where to save the model.