Validates if a MLFLow model can be loaded on a compute and is usable for inferencing.

Version: 0.0.16

Preview

View in Studio: https://ml.azure.com/registries/azureml/components/mlflow_model_local_validation/version/0.0.16

Name	Description	Type	Default	Optional	Enum
model_path	MLFlow model to be validated	mlflow_model
test_data_path	Test dataset for model inferencing	uri_file		True
column_rename_map	Provide mapping of dataset column names that should be renamed before inferencing. eg: col1:ren1; col2:ren2; col3:ren3	string		True
task_name	A Hugging face task on which model was trained on	string		True	['chat-completion', 'fill-mask', 'token-classification', 'question-answering', 'summarization', 'text-generation', 'text2text-generation', 'text-classification', 'translation', 'image-classification', 'image-classification-multilabel', 'image-object-detection', 'image-instance-segmentation', 'image-to-text', 'text-to-image', 'text-to-image-inpainting', 'image-text-to-text', 'image-to-image', 'zero-shot-image-classification', 'mask-generation', 'video-multi-object-tracking', 'visual-question-answering']

Name	Description	Type
mlflow_model_folder	Validated input model. Here input model is used to block further steps in pipeline job if local validation fails	uri_folder

azureml://registries/azureml/environments/python-sdk-v2/versions/23