# Import model packages into MLOps

> Import model packages into MLOps - Export a model created with DataRobot AutoML for import as a
> model package (.mlpkg file) in standalone MLOps environments.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-04-24T16:03:56.570334+00:00` (UTC).

## Primary page

- [Import model packages into MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html): Full documentation for this topic (HTML).

## Sections on this page

- [Export a model from AutoML](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#export-a-model-from-automl): In-page section heading.
- [Import a model package to a DataRobot MLOps-only environment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#import-a-model-package-to-a-datarobot-mlops-only-environment): In-page section heading.
- [Deploy a model package in MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#deploy-a-model-package-in-mlops): In-page section heading.

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/index.html): Linked from this page.
- [Deployment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/index.html): Linked from this page.
- [Register models](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/index.html): Linked from this page.
- [model package](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-create.html): Linked from this page.
- [deployment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/index.html): Linked from this page.
- [deployment creation settings](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/add-deploy-info.html): Linked from this page.
- [data drift](https://docs.datarobot.com/en/docs/classic-ui/mlops/monitor/data-drift.html): Linked from this page.
- [association ID](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/accuracy-settings.html#select-an-association-id): Linked from this page.

## Documentation content

# Import model packages into MLOps

> [!NOTE] Availability information
> This feature is only available for Self-Managed AI Platform users that require MLOps and AutoML to run in separate environments. The process outlined requires multiple feature preview flags. Contact your DataRobot representative for more information about this configuration.
> 
> Feature flags: Contact your DataRobot representative.

Models created with DataRobot AutoML can be [exported](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#export-a-model-from-automl) as a model package (.mlpkg file). This allows you to [import](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#import-a-model-package-to-a-datarobot-mlops-only-environment) a model package into standalone environments like DataRobot MLOps to make predictions and monitor the model. You can also [create a new deployment in MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-transfer.html#deploy-a-model-package-in-mlops) by importing a model package.

## Export a model from AutoML

You can export models created with AutoML from the Deploy tab on the model's Predict page.

> [!NOTE] Note
> The MLOps Package option on the Predict > Downloads tab directs you to Open the Deploy tab where you can deploy the model, add it to the Model Registry, or download the model package.

To export your model a model package (.mlpkg) file from DataRobot AutoML, add it to the Model Registry, or deploy it directly to the Deployments inventory, take the following steps:

1. On theLeaderboard, click the model you want to export.
2. ClickPredict > Deploy.
3. On theDeploytab, clickDownload .mlpkgto prepare the model package for export. View your progress in the Worker Queue underProcessing. After DataRobot finishes generating the model package, the download begins automatically, appearing in the downloads bar when complete. You now have an exported model package fully capable of deployment to a different environment (such as DataRobot MLOps).

## Import a model package to a DataRobot MLOps-only environment

To add an exported .mlpkg file to DataRobot MLOps as a [model package](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/registry/reg-create.html):

1. ClickModel Registryand then clickModel Packages.
2. On theModel Packagestab, clickAdd new packageand then clickImport model package file (.mlpkg).
3. Browse for and upload, or drag-and-drop, the .mlpkg file you exported from DataRobot AutoML. The model package is uploaded and extracted.
4. When this process completes, DataRobot adds your model package to theModel Packagestab, complete with the metadata for your model package.

## Deploy a model package in MLOps

To import your model into DataRobot MLOps, you can add it as a new [deployment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/index.html).

1. Navigate to theDeploymentspage and clickAdd deployment.
2. Under theAdd a modelheader, clickBrowseand clickLocal fileto upload your model package. You can also drag and drop a model package file into theAdd a modelbox.
3. After you upload a model, theDeploymentstab opens. NoteThe information under theModelheader appears automatically, as your model package contains that metadata. The model package also supplies the training data; you don't need to provide that information on this page. You can, however, add outcome data after you deploy the model.
4. Configure thedeployment creation settingsand decide if you want to allowdata drifttracking or require anassociation IDin prediction requests.
5. When you have added information about your data and your model is fully defined, you can clickDeploy modelat the top of the screen.
