-Gin supervised contextpred, Gin supervised edgepred, Gin supervised masking, and Gin supervised infomax: These models are based on pre-training a graph isomorphic network (GIN) on molecular data. The models have been trained on around 2 million graphs from the ChEMBL database, encompassing both graph-level and node-level prediction tasks. Graph-level pretraining is achieved through supervised learning, where the GIN is pre-trained to predict multiple molecular properties from the input graph.