Some steps of your machine learning pipeline might be more resource-intensive and require special hardware to execute. In such cases, you can specify the required resources for steps as follows:
Functional API
Class-based API
from zenml.steps import step, ResourceConfiguration
If you're using an orchestrator which doesn't support this feature or its underlying infrastructure doesn't cover your requirements, you can also take a look at step operators which allow you to execute individual steps of your pipeline in environments independent of your orchestrator.