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Merge pull request #218085 from santiagxf/santiagxf/azureml-mlflow-fix
Update how-to-mlflow-batch.md
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articles/machine-learning/batch-inference/how-to-mlflow-batch.md

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@@ -461,7 +461,7 @@ Use the following steps to deploy an MLflow model with a custom scoring script.
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# AZUREML_MODEL_DIR is an environment variable created during deployment
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# It is the path to the model folder
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model_path = os.path.join(os.environ["AZUREML_MODEL_DIR"], "model")
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model = mlflow.pyfunc.load(model_path)
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model = mlflow.pyfunc.load_model(model_path)
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def run(mini_batch):
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results = pd.DataFrame(columns=['file', 'predictions'])

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