A parallel MACE equivariant graph neural network for Si. This is a general purpose MLIP for Silicon, which can be employed for miscellaneous tasks owing to the broad dataset used in training. It was trained with a cutoff radius of 4 angstroms with max order of spherical harmonics set to 1. The hidden representation was set to 32x0e + 32x1o, meaning that it has equivariant symmetry equivalent to spherical harmonics of order 1 (1o). Number of graph convolutions to 3, correlation order was set to 2 (max tensor product body order = 3). For training, the GAP Si PRX (Bartók et al. Phys. Rev. X 8, 041048) dataset was used. The model was trained on energy and forces, with weight 1 and 1000 respectively. The model was trained till convergence, then the best model performing model on validation set selected.