The end goal for the proof of concept sprint is to serve a simple model over KFServing. To do that we need to create a simple model to serve.
I have no requirements for the model other than it be tree based and containerized per KF's guidelines.
calbon | |
Jan 22 2021, 6:33 PM |
F34013616: tfModel.zip | |
Jan 23 2021, 12:21 AM |
The end goal for the proof of concept sprint is to serve a simple model over KFServing. To do that we need to create a simple model to serve.
I have no requirements for the model other than it be tree based and containerized per KF's guidelines.
Status | Subtype | Assigned | Task | ||
---|---|---|---|---|---|
Resolved | None | T272917 Lift Wing proof of concept | |||
Resolved | • ACraze | T272728 Testing Model |
Here's a simple BoostedTreesClassifier that I trained on the Titanic dataset today. It's in the Tensorflow SavedModel format, which is required by KFServing/TFServing:
Code: https://gist.github.com/accraze/8fd30ba56bfd688ff9e5506976b86901
I plan to do a similar model in sklearn next week so we can test the multi-framework support.
We'll need to load the model binary from storage using something like pvc: https://github.com/kubeflow/kfserving/tree/master/docs/samples/storage/pvc