Traditionally, conformer sampling is refined via classical force fields, which yield a poor correlation with energies from more accurate quantum methods. On the other hand, geometry optimization with most density functional methods requires hours per conformer, making large-scale sampling prohibitive. Recently larger data sets have emerged, including this work, as well as the ANI-1x, GEOM, QCArchive, QMugs, and SPICE sets. The goal of this work is to show that while gas-phase quantum chemical geometries require substantial time to generate, such data sets can be used to augment or supplant traditional crystal structure sources to establish torsional preferences.