Create a Model
Creating a Model
A Model represents a machine learning model. Each Model has a type. Currently Merlin supports both standard model types (PyTorch, SKLearn, Tensorflow, and XGBoost) and user-defined models (PyFunc model).
Merlin also supports custom models. More info can be found here:
Conceptually, a Model in Merlin is similar to a class in programming languages. To instantiate a Model, you’ll have to create a Model Version.
merlin.set_model(<model_name>, <model_type>)
will set the active model to the name given by parameter. If the Model with given name is not found, a new Model will be created.
Creating a Model Version
A Model Version represents a snapshot of A particular Model iteration. A Model Version might contain artifacts which are deployable to Merlin. You'll also be able to attach information such as metrics and tags to a given Model Version.
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