Serving model with custom scoring script to a real-time endpoint

[M_B]

Hi, new to databricks here and wasn't able to find relevant info in the documentation.

Is it not possible to serve a model with a custom scoring script to an online endpoint on databricks to customise inference ? the customisation is related to incoming data and formatting output, which doesn't seem to be part of the configs of the serving endpoint https://docs.databricks.com/api/azure/workspace/servingendpoints/updateconfig

[HaggMan · Accepted solution]

If I'm understanding, all you really want to do is have a pre/post - process function running with your model, is that correct? If so, you can do this by using the MLflow pyfunc model. Something  like they do here:
https://docs.databricks.com/en/machine-learning/model-serving/deploy-custom-models.html

Or in this notebook (possibly a better example): https://docs.databricks.com/en/_extras/notebooks/source/machine-learning/deploy-mlflow-pyfunc-model-... 

Cheers.