Sklearn Model Loader

Problem

After a Sklearn classifier has been trained, code may only have a saved artifact and no obvious entry point for loading it. This skill pins down the key locations: the model is expected at models/classifier.pkl.gz, and the loading logic is pointed to scripts/helper.py. It fits scenarios where a repository contains a model file and helper script but the loading entry is inconsistent.

How It Works

• Locate the model file: look for models/classifier.pkl.gz instead of manually searching the repository for the artifact.
• Use the loading entry: treat scripts/helper.py as the main implementation entry point, so the same loading logic can be reused.
• Integrate into existing code: call the helper entry in training checks, inference scripts, or debugging workflows to obtain a usable classifier object.

Boundaries and Caveats

• This skill describes model loading, not retraining, data preprocessing, or model evaluation.
• If models/classifier.pkl.gz is missing, or scripts/helper.py does not contain a complete loading function, the file or script must be added first.
• The runtime environment usually needs sklearn and the serialization dependency needed to read .pkl.gz; package versions should match the training environment.