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Arxiv
1d
331
Image Credit: Arxiv
GP-MoLFormer: A Foundation Model For Molecular Generation
- GP-MoLFormer is an autoregressive molecular string generator trained on over 1.1 billion chemical SMILES.
- It performs well on three different generative tasks: de novo generation, scaffold-constrained molecular decoration, and property-guided optimization.
- GP-MoLFormer demonstrates its general utility and compares favorably to existing baselines.
- The model shows strong memorization of training data, impacted by the quality and scale of the training data.
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