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tags: |
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- molecular language model |
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--- |
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# MolGen |
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MolGen was introduced in the paper ["Molecular Language Model as Multi-task Generator"](https://arxiv.org/pdf/2301.11259.pdf) and first released in [this repository](https://github.com/zjunlp/MolGen). It is a pre-trained molecular generative model built using the 100\% robust molecular language representation, SELFIES. |
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## Model description |
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MolGen is the first pre-trained model that only produces chemically valid molecules. |
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With a training corpus of over 100 million molecules in SELFIES representation, MolGen learns the intrinsic structural patterns of molecules by mapping corrupted SELFIES to their original forms. |
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Specifically, MolGen employs a bidirectional Transformer as its encoder and an autoregressive Transformer as its decoder. |
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Through its carefully designed multi-task prefix tuning (MPT), MolGen can generate molecules with desired properties, making it a valuable tool for molecular optimization. |
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### BibTeX entry and citation info |
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```bibtex |
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@article{fang2023molecular, |
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title={Molecular Language Model as Multi-task Generator}, |
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author={Fang, Yin and Zhang, Ningyu and Chen, Zhuo and Fan, Xiaohui and Chen, Huajun}, |
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journal={arXiv preprint arXiv:2301.11259}, |
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year={2023} |
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} |
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``` |
