Training jobs saving to the registry
The model registry is a natural fit for training jobs. In your training job, call
add_model to store your trained model into the registry.
Your model will then be available for further analysis in your notebook, or for inferences in your deployments.
If your training job was set to save changes on success, then the updated models will be available in the registry with
get_model. If not, the models will be available as pending changes in the job, which you can retrieve with
For more information, see the Training Jobs section.