In the pre-training step, 646,907 MOFs generated by PORMAKE were used as the dataset for the generator. Each organic linker was decomposed into scaffold fragments with the BRICS algorithm, which allow splitting molecules into chemically semantic fragments. For each organic linker, if the decomposed fragments were a subset of other fragments, the subsets were dismissed. And the maximum number of scaffold fragments was set to four. The smaller fragments were omitted if a molecule was decomposed into more than four scaffold fragments. The scaffold fragments were randomly combined and joined in SELFIES to build a batch of scaffolds. Finally, a dataset of 1,540,889/385,223/10,000 (train/validation/test) was created for the generator. For the predictor, Widom calculations were implemented to compute the CO 2 heat of adsorption and CO 2 /H 2 O selectivity data for ∼30, 000 MOFs generated by PORMAKE. They were split in the ratio 8:1:1 (train:validation:test).