This is a machine learning model that predicts IUPAC names from InChI. It was trained on a dump of PubChem's database, and has a transformer encoder-decoder architecture. Instructions Requires: Python >= 3.6 PyTorch == 1.6.0 1. Install OpenNMT-py version 2.0.0: pip install OpenNMT-py==2.0.0 2. Prepare InChI to be translated by splitting into individual characters separated by whitespace and saving in a text file. You can predict multiple IUPAC names by having one InChI per line (see example.inchi for reference). 3. Perform the prediction with the supplied model file: onmt_translate --beam_size 10 --length_penalty wu --alpha 1.0 --model inchi2iupac_step_259200.pt --src <infile> --max_length 300 --output <outfile>