Machine learning model layer

Abstract

Techniques are disclosed that pertain to facilitating the execution of machine learning (ML) models. A computer system may implement an ML model layer that permits ML models built using any of a plurality of different ML model frameworks to be submitted without a submitting entity having to define execution logic for a submitted ML model. The computer system may receive, via the ML model layer, configuration metadata for a particular ML model. The computer system may then receive a prediction request from a user to produce a prediction based on the particular ML model. The computer system may produce a prediction based on the particular ML model. As a part of producing that prediction, the computer system may select, in accordance with the received configuration metadata, one of a plurality of types of hardware resources on which to load the particular ML model.