metadata
license: mit
library_name: transformers
tags:
- chemistry
- cheminformatics
- natural-products
- smiles
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")