Overview Use Cases Connectors Authentication Getting Started with the Python SDK API Reference ai_agents ai_chat algorithm annotations application_connectors batch_prediction code_completion custom_loss_function custom_metric database_connectors dataset deployment deployment_conversations docstore document_retrievers documentation eda external_app feature_drift feature_group feature_group_row_process feature_group_template file_connectors graph_dashboard holdout_analysis llm_apps model createModelFromPython createTrainTestDataSplitFeatureGroup deleteModel deleteModelVersion describeModel describeModelArtifactsExport describeModelVersion describeTrainTestDataSplitFeatureGroup describeTrainTestDataSplitFeatureGroupVersion exportCustomModelVersion exportModelArtifactAsFeatureGroup getCustomTrainFunctionInfo getFeatureGroupSchemasForModelVersion getFeatureImportanceByModelVersion getModelMetrics getTrainingConfigOptions getTrainingDataLogs getTrainingLogs listModelArtifactsExports listModelVersions listModels renameModel retrainModel setDefaultModelAlgorithm setModelObjective setModelPredictionParams setModelTrainingConfig trainModel updatePythonModel updatePythonModelGit updatePythonModelZip model_monitoring module natural_language_explanation organization pipelines predict prediction_operator project python_function refresh secrets streaming streaming_connectors upload webhooks API Classes API Inputs Documentation Chat Bot API Search Video Tutorials ChatLLM

Method

deleteModelVersion DELETE

Copy DELETE

Deletes the specified model version. Model versions which are currently used in deployments cannot be deleted.

Arguments:

REQUIRED	KEY	TYPE	DESCRIPTION
Yes	modelVersion	str	The unique identifier of the model version to delete.

Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY	TYPE	DESCRIPTION
success	Boolean	true if the call succeeded, false if there was an error

Exceptions:

TYPE	WHEN
ConflictError	The model version is currently used in one or more deployments.

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