Export the scikit-learn estimators and the Hugging Face models

### Task Summary

The scikit-learn estimators implement `StandaloneCodeGenerator`. They are fitted on one port and score on the other, so the script holds both frames and narrows each by the same rule: a fit and a score taken on different columns would compare two different models.

The four Hugging Face models declare the column types they take, and the iris regression keeps the row when a petal measurement is empty rather than ending the run on it.

Sklearn Prediction and Sklearn Testing are reported as unverifiable rather than exported blind: each consumes a fitted model on an input port, and a fixture written from the JVM cannot carry a live Python object.

Step 20 of 27 in #8325. It needs #8327 for the trait. The two behaviour changes are filed separately as #8316 and #8056 and close with this work.