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Tools for interpretability analysis of physical AI models, including sparse autoencoders and attention mapping
pip install physical-ai-interpretability
PyPI declares 27 unique dependency rules for this release. Environment markers are shown when supplied by the project.
>=1.12.0>=1.20.0>=4.60.0>=0.3.0>=1.3.0>=0.2.4>=4.5.0>=0.12.0The compact report shows 25 of 27 declarations. The interactive dependency graph loads the complete metadata.
physical-ai-interpretability publishes 1 wheel and 1 source archive for version 0.1.4. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.11.
PyPI lists 5 releases with files. The first dated release is ; 5 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .