HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract)
DOI:
https://doi.org/10.1609/aaai.v36i11.21611Keywords:
Transformers, Pre-trained Methods, Molecular Property PredictionAbstract
Large-scale transformer-based methods are gaining popularity as a tool for predicting the properties of chemical compounds, which is of central importance to the drug discovery process. To accelerate their development and dissemination among the community, we are releasing HuggingMolecules -- an open-source library, with a simple and unified API, that provides the implementation of several state-of-the-art transformers for molecular property prediction. In addition, we add a comparison of these methods on several regression and classification datasets. HuggingMolecules package is available at: github.com/gmum/huggingmolecules.Downloads
Published
2022-06-28
How to Cite
Gaiński, P., Maziarka, Łukasz, Danel, T., & Jastrzebski, S. (2022). HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12949-12950. https://doi.org/10.1609/aaai.v36i11.21611
Issue
Section
AAAI Student Abstract and Poster Program