HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract)

Authors

  • Piotr Gaiński Jagiellonian University Ardigen
  • Łukasz Maziarka Jagiellonian University
  • Tomasz Danel Jagiellonian University Ardigen
  • Stanisław Jastrzebski Molecule.one

DOI:

https://doi.org/10.1609/aaai.v36i11.21611

Keywords:

Transformers, Pre-trained Methods, Molecular Property Prediction

Abstract

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.

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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