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--- |
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license: mit |
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language: |
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- en |
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--- |
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# Multitask Text and Chemistry T5 |
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Multitask Text and Chemistry T5 : a multi-domain, multi-task language model to solve a wide range of tasks in both the chemical and natural language domains. Published by [Christofidellis et al.](https://arxiv.org/pdf/2301.12586.pdf) |
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**Model Details**: The Multitask Text and Chemistry T5 variant trained using <em>t5-small</em> as its pretrained based and the <em>augmented dataset</em>. |
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**Developers**: Dimitrios Christofidellis*, Giorgio Giannone*, Jannis Born, Teodoro Laino and Matteo Manica from IBM Research and Ole Winther from Technical University of Denmark. |
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**Distributors**: Model natively integrated into GT4SD. |
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**Model date**: 2023. |
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**Model type**: A Transformer-based language model that is trained on a multi-domain and a multi-task dataset by aggregating available datasets |
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for the tasks of Forward reaction prediction, Retrosynthesis, Molecular captioning, Text-conditional de novo generation and Paragraph to actions. |
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**Information about training algorithms, parameters, fairness constraints or other applied approaches, and features**: |
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N.A. |
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**Paper or other resource for more information**: |
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The Multitask Text and Chemistry T5 [Christofidellis et al.](https://arxiv.org/pdf/2301.12586.pdf) |
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**License**: MIT |
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**Where to send questions or comments about the model**: Open an issue on [GT4SD repository](https://github.com/GT4SD/gt4sd-core). |
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## Citation |
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```bib |
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@article{christofidellis2023unifying, |
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title={Unifying Molecular and Textual Representations via Multi-task Language Modelling}, |
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author={Christofidellis, Dimitrios and Giannone, Giorgio and Born, Jannis and Winther, Ole and Laino, Teodoro and Manica, Matteo}, |
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journal={arXiv preprint arXiv:2301.12586}, |
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year={2023} |
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} |
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``` |
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*equal contribution |
