The ANI family of atomistic neural network potentials are based off the Behler-Parrinello Previous work has shown that the ANI architecture can be extended to the prediction of atomic properties. Here, we use the ANI-MBIS-q model to predict atomic charges of the ML subsystem on-the-fly. This model was trained on MBIS atomic charges corresponding to ωB97X/6-31G* electron densities, using the loss function: