Factual package intelligence from PyPI
scikit-learn estimators backed by language models: classifiers, regressors, imputers and oversamplers.
pip install scikit-lm
PyPI declares 40 unique dependency rules for this release. Environment markers are shown when supplied by the project.
>=0.14>=2.0>=2.2>=1.6The compact report shows 12 of 40 declarations. The interactive dependency graph loads the complete metadata.
scikit-lm publishes 1 wheel and 1 source archive for version 0.0.1. Wheel platform tags: any.
Declared Python classifiers: 3.12, 3.13, 3.14.
PyPI lists 1 release with files. The first dated release is ; 1 release falls within the 365 days preceding the latest dated release. The current release files were uploaded on .