Versioning support in the Model Registry¶

The Model Registry is an organizational hub for various models used in DataRobot, where you can access models as deployment-ready model packages. Now available for Public Preview, the Model Registry > Registered Models page provides an additional layer of organization to your models.

On this page, you can group model packages into registered models, allowing you to categorize them based on the business problem they solve. Registered models can contain:

• DataRobot, custom, and external models

• Challenger models (alongside the champion)

• Automatically retrained models.

Once you add registered models, you can search, filter, and sort them. You can also share your registered models (and the versions they contain) with other users.

Add registered models¶

You can register DataRobot, custom, and external model packages. When you add model packages to the Registered Models page, you can create a new registered model (version one) or save the model package as a new version of an existing registered model. Model packages added as versions of the same registered model must have the same target type, target name, and, if applicable, target classes and time series settings.

Each registered model on the Registered Models page must have a unique name. If you choose a name that exists anywhere within your organization when creating a new registered model, the Model registration failed warning appears. Use a different name or add this model as a new version of the existing registered model.

Add a DataRobot model¶

To add a DataRobot model as a registered model or version:

1. Navigate to Models > Leaderboard.

2. From the Leaderboard, click the model you want to register and click Predict > Deploy.

3. Under Deploy model, click Add to Model Registry.

   

4. In the Register new model dialog box, configure the following:

   

   Field	Description
   Register model	Select one of the following: Register new model: Create a new registered model. This creates the first version (V1). Save as a new version to existing model: Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.
   Registered model name / Registered Model	Do one of the following: Registered model name: Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the Model registration failed warning appears. Registered Model: Select the existing registered model you want to add a new version to.
   Registered model version	Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always V1 when you select Register a new model.
   Prediction threshold	For binary classification models. Enter the value a prediction score must exceed to be assigned to the positive class. The default value is 0.5. For more information, see Prediction thresholds.
   Optional settings
   Version description	Describe the business problem these model packages solve, or, more generally, the relationship between them.
   Tags	Click + Add item and enter a Key and a Value for each key-value pair you want to tag the model version with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to V1.

5. Click Add to registry.

Add a custom model¶

To add a custom model as a registered model or version:

1. Navigate to Model Registry > Custom Model Workshop.

2. From the Custom Model Workshop, click the model you want to register and, on the Assemble tab, click Add to Model Registry.

   

3. In the Register new model dialog box, configure the following:

   

   Field	Description
   Register model	Select one of the following: Register new model: Create a new registered model. This creates the first version (V1). Save as a new version to existing model: Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.
   Registered model name / Registered Model	Do one of the following: Registered model name: Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the Model registration failed warning appears. Registered Model: Select the existing registered model you want to add a new version to.
   Registered model version	Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always V1 when you select Register a new model.
   Optional settings
   Version description	Describe the business problem these model packages solve, or, more generally, the relationship between them.
   Tags	Click + Add item and enter a Key and a Value for each key-value pair you want to tag the model version with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to V1.

4. Click Add to registry.

Add an external model¶

To add an external model as a registered model or version:

1. On the Model Registry > Registered Models page, click Register New Model > External model.

   

2. In the Register new external model dialog box, configure the following:

   

   Field	Description
   Package Name	The name of the model package.
   Package description (optional)	Information to describe the model package.
   Model location (optional)	The location of the model running outside of DataRobot. Describe the location as a filepath, such as folder1/opt/model.tar.
   Build Environment	The programming language in which the model was built.
   Training data (optional)	The filename of the training data, uploaded locally or via the AI Catalog. Click Clear selection to upload and use a different file.
   Holdout data (optional)	The filename of the holdout data, uploaded locally or via the AI Catalog. Use holdout data to set an accuracy baseline and enable support for target drift and challenger models.
   Target	The dataset column name the model will predict on.
   Prediction type	The type of prediction the model is making, either binary classification or regression. For a classification model, you must also provide the positive and negative class labels and a prediction threshold.
   Prediction column	The column name in the holdout dataset containing the prediction result.

   If registering a time series model, select the This is a time series model checkbox and configure the following fields:

   

   Field	Description
   Forecast date feature	The column in the training dataset that contains date/time values used by DataRobot to detect the range of dates (the valid forecast range) available for use as the forecast point.
   Date/time format	The format used by the date/time features in the training dataset.
   Forecast point feature	The column in the training dataset that contains the point from which you are making a prediction.
   Forecast unit	The time unit (seconds, days, months, etc.) that comprise the time step.
   Forecast distance feature	The column in the training dataset containing a unique time step—a relative position—within the forecast window. A time series model outputs one row for each forecast distance.
   Series identifier (optional, used for multiseries models)	The column in the training dataset that identifies which series each row belongs to.

   Finally, configure the registered model settings:

   Field	Description
   Register model	Select one of the following: Register new model: Create a new registered model. This creates the first version (V1). Save as a new version to existing model: Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.
   Registered model name / Registered Model	Do one of the following: Registered model name: Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the Model registration failed warning appears. Registered Model: Select the existing registered model you want to add a new version to.
   Registered model version	Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always V1 when you select Register a new model.
   Optional settings
   Version description	Describe the business problem these model packages solve, or, more generally, the relationship between them.
   Tags	Click + Add item and enter a Key and a Value for each key-value pair you want to tag the model version with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to V1.

3. Once all fields for the external model are defined, click Register.

Access registered models and versions¶

On the Registered Models page, you can sort registered models by Name or Last modified. In a registered model, on the Versions tab, you can sort versions by Name, Created at, Last updated at, or Model type:

In the top-left corner of the Registered Models page, you can:

• Click Search and enter the registered model name to locate it on the Registered Models page.

• Click Filters to enable, modify, or clear filters on the Registered Models page. You can filter by Target name, Target type, Created by, Created between, and Modified between. This control filters on registered models:

  

View model and version information¶

Once you locate the registered model or model version you are looking for, you can access a variety of information about the registered model or version.

Model info¶

Click a registered model to open the details panel. From that panel, you can access the following tabs:

Tab	Description
Versions	View all model versions for a registered model and the associated creation and status information. To open the version in the current tab, click the row for the version you want to access. To open the version in a new tab, click the open icon () next to the Type column for the version you want to access.
Deployments	View all model deployments for a registered model and the associated creation and status information. You can click a name in the Deployment column to open that deployment.
Model Info	View the registered model ID, Name, Latest Version, Created By username, Created date, Last Modified date, Target Type, and Target Name. You can click the pencil icon () next to Name to edit the registered model's name.

Version info¶

To open the registered model version, do either of the following:

• To open the version in the current tab, click the row for the version you want to access.

• To open the version in a new tab, click the open icon () next to the Type column for the version you want to access.

Deploy registered models¶

You can deploy a registered model at any time from the Registered Models page. To do that, you must open a custom model version:

1. On the Registered Models page, click the registered model containing the model version you want to deploy.

2. To open the registered model version, do either of the following:

   

   • To open the version in the current tab, click the row for the version you want to access.

   • To open the version in a new tab, click the open icon () next to the Type column for the version you want to access.

3. In the version header, click Deploy, and then configure the deployment settings.

   

Manage registered models¶

You can Share or Delete registered models from the menu icon () in the last column of the Registered Models page: