components text_classification_model_import - Azure/azureml-assets GitHub Wiki

Text Classification Model Import



Component to import PyTorch / MLFlow model. See docs to learn more.

Version: 0.0.51

View in Studio:


huggingface id

NOTE The pytorch_model_path or mlflow_model_path takes precedence over huggingface_id

Name Description Type Default Optional Enum
huggingface_id The string can be any valid Hugging Face id from the Hugging Face models webpage. Models from Hugging Face are subject to third party license terms available on the Hugging Face model details page. It is your responsibility to comply with the model's license terms. string True

PyTorch model as input This is nothing but huggingface model folder. Here's the link to the example model folder - bert-base-uncased. Additionally, the model folder MUST contain the file finetune_args.json with model_name_or_path as one of the keys of the dictionary

Name Description Type Default Optional Enum
pytorch_model_path Pytorch model asset path custom_model True

MLflow model as an input This is also a huggingface model folder expect that the folder structure is slightly different. You could invoke a model import pipeline to convert the standard huggingface model into MLflow format. Please refer to this notebook for steps to do the same NOTE The pytorch_model_path take priority over mlflow_model_path, in case both inputs are passed

Name Description Type Default Optional Enum
mlflow_model_path MLflow model asset path mlflow_model True

Output of validation component

Name Description Type Default Optional Enum
validation_output Validation status. uri_file True


Name Description Type
output_dir Path to output directory which contains the component metadata and the model artifacts folder uri_folder



⚠️ ** Fallback** ⚠️