Associate a pipeline with a Model

The most common use-case for a Model is to associate it with a pipeline.

from zenml import pipeline
from zenml import Model

@pipeline(
    model=Model(
        name="ClassificationModel",  # Give your models unique names
        tags=["MVP", "Tabular"]  # Use tags for future filtering
    )
)
def my_pipeline():
    ...

This will associate this pipeline with the model specified. In case the model already exists, this will create a new version of that model.

In case you want to attach the pipeline to an existing model version, specify this as well.

from zenml import pipeline
from zenml import Model
from zenml.enums import ModelStages

@pipeline(
    model=Model(
        name="ClassificationModel",  # Give your models unique names
        tags=["MVP", "Tabular"],  # Use tags for future filtering
        version=ModelStages.LATEST  # Alternatively use a stage: [STAGING, PRODUCTION]]
    )
)
def my_pipeline():
    ...

Feel free to also move the Model configuration into your configuration files:

...

model:
  name: text_classifier
  description: A breast cancer classifier
  tags: ["classifier","sgd"]

...