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guides/md/orbax_checkpoint.md

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@@ -57,7 +57,6 @@ We need to create two main utilities to manage Orbax checkpointing in Keras:
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`orbax.checkpoint.CheckpointManager` for Keras models.
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`KerasOrbaxCheckpointManager` uses `Model`'s `get_state_tree` and
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`set_state_tree` APIs to save and restore the model variables.
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2. `OrbaxCheckpointCallback`: A Keras callback that uses
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`KerasOrbaxCheckpointManager` to automatically save and restore model states
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during training.

guides/orbax_checkpoint.py

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@@ -54,7 +54,6 @@
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`orbax.checkpoint.CheckpointManager` for Keras models.
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`KerasOrbaxCheckpointManager` uses `Model`'s `get_state_tree` and
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`set_state_tree` APIs to save and restore the model variables.
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2. `OrbaxCheckpointCallback`: A Keras callback that uses
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`KerasOrbaxCheckpointManager` to automatically save and restore model states
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during training.

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