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---
license: cc-by-nc-4.0
language:
- en
library_name: transformers
tags:
- chemistry
- biology
---
Chemlactica-125m is a continually pretrained [galactica-125m](https://huggingface.co/facebook/galactica-125m) model for organic molecules.
It is pretrained on (soon-to-be-released) 40B tokens covering 110M+ molecules from PubChem as well as their chemical properties
(molecular weight, synthetic accessibility score, drug-likeness etc.)
and similarities (Tanimoto distance between ECFP fingerprints).
Example prompts:
`</s>[START_SMILES]CC(=O)OC1=CC=CC=C1C(=O)O[END_SMILES][SAS]` will attempt to predict the synthetic accessibility score of the given molecule.
`</s>[SAS]2.25[/SAS][SIMILAR]0.62 CC(=O)OC1=CC=CC=C1C(=O)O[/SIMILAR][START_SMILES]` will attempt to generate a molecule that has 2.25 SAS score and
has a 0.62 similarity score to the given molecule.
The model can be wrapped into an optimization loop to traverse the chemical space with evolving prompts.
A preprint with the details of the model and an optimization algorithm built on top of this model that sets state-of-the-art on Practical Molecular Optimization
and other benchmarks will be released soon.
Few notes:
* All queries should start with `</s>` symbol.
* All numbers are rounded to two decimal points.
* All SMILES are canonicalized using `rdkit`.
* Available tags: `[CLOGP]`, `[WEIGHT]`, `[QED]`, `[SAS]`, `[TPSA]`, `[RINGCOUNT]`, `[SIMILAR]`...
The model is part of the 3-model family: [Chemlactica-125M](https://huggingface.co/yerevann/chemlactica-125m),
[Chemlactica-1.3B](https://huggingface.co/yerevann/chemlactica-1.3b) and [Chemma-2B](https://huggingface.co/yerevann/chemma-2b).
We are looking forward to see the community using the model in new applications and contexts. |