| 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`](https://huggingface.co/kohbanye/SmilesTokenizer_PubChem_1M). | |
| ## Usage | |
| ```python | |
| 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: | |
| ```python | |
| from transformers import AutoModelForCausalLM | |
| model = AutoModelForCausalLM.from_pretrained("kohbanye/clamnp", subfolder="natural") | |
| ``` | |