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  This model corresponds to the MolDeBERTa tiny architecture pretrained on the 10M dataset using the MLM pretraining objective.
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- \[[Github Repo](https://github.com/pcdslab/MolDeBERTa)\] | \[[Dataset on HuggingFace](https://huggingface.co/datasets/SaeedLab/MolDeBERTa)\] | \[[Model Collection](https://huggingface.co/collections/SaeedLab/moldeberta)\] | \[[Cite](#citation)\]
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  ## Abstract
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  ## Citation
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- The paper is under review. As soon as it is accepted, we will update this section.
 
 
 
 
 
 
 
 
 
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  ## License
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  This model corresponds to the MolDeBERTa tiny architecture pretrained on the 10M dataset using the MLM pretraining objective.
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+ \[[Paper](https://www.biorxiv.org/content/10.64898/2026.02.15.706011v2)\] | \[[Github Repo](https://github.com/pcdslab/MolDeBERTa)\] | \[[Dataset on HuggingFace](https://huggingface.co/datasets/SaeedLab/MolDeBERTa)\] | \[[Model Collection](https://huggingface.co/collections/SaeedLab/moldeberta)\] | \[[Cite](#citation)\]
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  ## Abstract
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  ## Citation
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+ ```bibtex
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+ @article{moldeberta2026,
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+ title = {MolDeBERTa: Foundational Model for Physicochemical and Substructure-Informed Molecular Representation Learning},
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+ author = {Oliveira, Gabriel Bianchin de and Saeed, Fahad},
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+ journal = {bioRxiv},
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+ year = {2026},
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+ doi = {10.64898/2026.02.15.706011},
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+ url = {https://doi.org/10.64898/2026.02.15.706011}
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+ }
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+ ```
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  ## License
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