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--- |
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license: cc-by-nc-4.0 |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- chemistry |
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- biology |
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--- |
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Chemma-2B is a continually pretrained [gemma-2b](https://huggingface.co/google/gemma-2b) model for organic molecules. |
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It is pretrained on [40B tokens covering 110M+ molecules from PubChem](https://huggingface.co/datasets/yerevann/PubChemForLM) as well as their chemical properties |
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(molecular weight, synthetic accessibility score, drug-likeness etc.) |
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and similarities (Tanimoto distance between ECFP fingerprints). |
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Example prompts: |
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`</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. |
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`</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 |
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has a 0.62 similarity score to the given molecule. |
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The model can be wrapped into an optimization loop to traverse the chemical space with evolving prompts. See the [code on GitHub](https://github.com/YerevaNN/ChemLactica). |
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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 |
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Practical Molecular Optimization and other benchmarks is [available on arxiv](https://arxiv.org/abs/2407.18897). |
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Few notes: |
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* All queries should start with `</s>` symbol. |
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* All numbers are rounded to two decimal points. |
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* All SMILES are canonicalized using `rdkit`. |
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* Available tags: `[CLOGP]`, `[WEIGHT]`, `[QED]`, `[SAS]`, `[TPSA]`, `[RINGCOUNT]`, `[SIMILAR]`... |
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The model is part of the 3-model family: [Chemlactica-125M](https://huggingface.co/yerevann/chemlactica-125m), |
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[Chemlactica-1.3B](https://huggingface.co/yerevann/chemlactica-1.3b) and [Chemma-2B](https://huggingface.co/yerevann/chemma-2b). |
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We are looking forward to see the community using the model in new applications and contexts. |
