kohbanye/clamnp

CLaM-NP

SMILES language models for natural-product-likeness scoring (CLaM-NP Score).

This repository hosts up to three causal language models, one per subfolder:

Subfolder	Training data	Role
natural	COCONUT	P(x | natural)
synthetic	ZINC22	P(x | synthetic)
general	ChEMBL	P(x | general) — stabilizer

Tokenizer: kohbanye/SmilesTokenizer_PubChem_1M.

Usage

from clamnp import CLaMNPScorer

scorer = CLaMNPScorer.from_pretrained()          # this repo
print(scorer.score("CC(=O)Oc1ccccc1C(=O)O"))         # CLaM-NP Score

Or load a single model directly:

from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("kohbanye/clamnp", subfolder="natural")