xvzemin/tace

TACE is a machine-learning interatomic-potential toolkit built around tensor atomic and edge cluster expansion models. Its main workflow is to read and prepare atomistic structures, train or fine-tune an equivariant model against requested properties, then evaluate or deploy predictions through simulation interfaces. The graph also preserves documented model variants, physical-property/plugin capabilities, and EquivariantX’s lower-level equivariant and accelerated-computation layer. Source excerpts are partial, so uncertain internal call wiring is omitted; documented capabilities are shown without asserting uninspected implementation details.