error status 400 calling serving model endpoint invocation using personal access token on Azure Databricks
Hi all, I've deployed a model, moved it to production and served it (mlflow), but when testing it in the python notebook I get a 400 error. code/details below:import osimport requestsimport jsonimport pandas as pdimport numpy as np# Create two record...
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data_json in the score_model function should be defined as followsds_dict = {"dataframe_split": dataset.to_dict(orient='split')} if isinstance(dataset, pd.DataFrame) else create_tf_serving_json(dataset)
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