SMILES Pair Encoding (JCIM) first learns a vocabulary of high frequency SMILES substrings from a large chemical dataset (e.g., ChEMBL) and then tokenizes SMILES based on the learned vocabulary for ...
4.2 Implementation details The model that was used in this experiment was coded in Python as a PyTorch-based deep learning pipeline and scikit-learn-based evaluation performance. Training used NVIDIA ...
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