Model Management#

Use Checkpoints#

When a model is trained with Determined, checkpoints are automatically saved to external storage. These checkpoints can then be exported for use outside Determined. See Checkpoints for details.

Archive Experiments#

After training, you can archive experiments to clean up your list of experiments. Archiving is designed to make it easier to organize experiments by omitting information about experiment runs that are no longer relevant (e.g., training jobs that failed with an error or jobs submitted as part of the model development process). When an experiment is archived, it is hidden from the default view in both the WebUI and the Determined CLI, but all of the metadata associated with the experiment (including checkpoints) is preserved. An experiment can subsequently be unarchived if desired, without losing any of the experiment’s metadata.

Delete Checkpoints#

The best way to delete a checkpoint is to modify the garbage collection policy of the experiment that created the checkpoint. For example, to delete all of the experiments associated with an experiment, run:

det experiment set gc-policy --save-experiment-best 0 --save-trial-best 0 --save-trial-latest 0 <experiment-id>

Manage Trained Models#

Determined includes a built-in model registry to manage trained models and their respective versions.