ersilia-os/chempfn
Ensemble-based, size-agnostic wrapper for the TabPFN classifier
This project helps medicinal chemists and cheminformaticians classify chemical compounds based on their molecular structure. You provide a list of chemical structures (SMILES data), and it predicts a category or property for each, such as whether a compound is antimicrobial. It's designed for researchers working with chemical datasets who need fast, accurate classification without extensive model tuning.
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Use this if you need to quickly classify chemical compounds from SMILES data into distinct categories, especially for small-to-medium datasets, without manually featurizing your molecules.
Not ideal if you require extremely fast prediction times for very large datasets, as prediction speed can vary depending on configuration and hardware.
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GPL-3.0
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Last pushed
May 18, 2024
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