Model version details

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From the Vertex AI Model Registry, you can view specific metadata for a model version. From a model version's details page, you can choose to deploy and test your model, set up batch prediction, and evaluate depending on the model type. You can also view the dataset used to train the model version directly from the version details page.

View model version details

Console

  1. In the Google Cloud console, go to the Vertex AI Model Registry page.

    Go to the Model Registry page

  2. Select the model that you want to view.

  3. Select the number (1) from the Default version column. This links directly to the version details page for your default version. Note: the number in the Default version column represents which model is assigned the default alias. If for example, your third model version is assigned the alias, (3) appears in that column.

Click on the default model to view details page.

API

Python


from google.cloud import aiplatform


def get_model_version_info_sample(
    model_id: str, version_id: str, project: str, location: str
):
    """
    Get model version info.
    Args:
        model_id: The ID of the model.
        version_id: The version ID of the model version.
        project: The project ID.
        location: The region name.
    Returns:
        VersionInfo resource.
    """

    # Initialize the client.
    aiplatform.init(project=project, location=location)

    # Initialize the Model Registry resource with the ID 'model_id'.The parent_name of Model resource can be also
    # 'projects/<your-project-id>/locations/<your-region>/models/<your-model-id>'
    model_registry = aiplatform.models.ModelRegistry(model=model_id)

    # Get model version info with the version 'version_id'.
    model_version_info = model_registry.get_version_info(version=version_id)

    return model_version_info