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----
-# language: SELFIES
-tags:
-- molecular language model
-
----
-	
-# MolGen
-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.
-## Model description
-MolGen is the first pre-trained model that only produces chemically valid molecules. 
-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.
-Specifically, MolGen employs a bidirectional Transformer as its encoder and an autoregressive Transformer as its decoder.
-Through its carefully designed multi-task prefix tuning (MPT), MolGen can generate molecules with desired properties, making it a valuable tool for molecular optimization.
-
-
-### BibTeX entry and citation info
-```bibtex
-@article{fang2023molecular,
-  title={Molecular Language Model as Multi-task Generator},
-  author={Fang, Yin and Zhang, Ningyu and Chen, Zhuo and Fan, Xiaohui and Chen, Huajun},
-  journal={arXiv preprint arXiv:2301.11259},
-  year={2023}
-}
-```