New Release! Git-backed Machine Learning Model Registry for all your model management needs.
To manage model lifecycle, you can assign stages (such as development
,
staging
, production
, etc.) to specific model versions.
To assign a stage to a model version, Iterative Studio uses GTO to create an annotated Git tag with the specified stage and version number. Refer the GTO docs to see the exact format of the Git tag.
You can write CI/CD actions that can actually deploy the models to the different deployment environments upon the creation of a new Git tag for stage assignment. For that, you can leverage any ML model deployment tool, such as MLEM.
You can assign stages using the GTO CLI. To assign stages using Iterative Studio, watch this tutorial video or read on below:
On the models dashboard, open the 3-dot menu for the model whose version you
want to assign the stage to. Then, click on Assign stage
. This action can
also be initiated from the model details page or from the related project’s
experiment table - look for the Assign stage
button or icon.
Select the version to which you want to assign the stage.
Enter the stage name (eg, development
, staging
, production
).
You can define the list of stages in the .gto
config file, which is a
yaml
structured file that allows you to specify artifact types and stages.
If you have defined the stages in this file, then you can assign to these
stages only. But if you have not defined the list of stages, you can enter
any string as the stage name. Note the following:
Optionally, provide a Git tag message.
Click on Assign stage
.
Once the action is successful, the stage assignment will show up in the
Stages
column of the models dashboard.
If you open the model details page, the stage assignment will be visible in
the model History
section as well as in the Stages
section.
If you go to your Git repository, you will see that a new Git tag referencing the selected version and stage has been created, indicating the stage assignment.