What types of artifact files can I save using MLflow?
I know that it is possible to log models as artifacts during an MLflow run. Can I save other types of files as well?
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I know that it is possible to log models as artifacts during an MLflow run. Can I save other types of files as well?
For me, the main benefit is that it is little or no work to enable. For example, when autologging is enabled for a library like sklearn or Pytorch, a lot of information about a model is captured with no additional steps. Further in Databricks, the tr...