Download and extract the compressed file qm9.tar.gz from this shared Drive putting them in the subdirectory data.
Checking if conformers match its SMILES string. You can check all valid conformers by running
python standardize_confs.py
This saves all valid conformers into the file specified by argument --out_dir in script file standardize_confs.py
You can train the model by running
python train.py
All tunable parameters and directory to datasets can be found in utils/parsing.py