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This is a variant of the [google/mt5-base](https://huggingface.co/google/mt5-base) model, in which Ukrainian and 9% English words remain.
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This model has 252M parameters - 43% of the original size.
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Special thanks for the practical example and inspiration: [cointegrated ](https://huggingface.co/cointegrated)
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This is a variant of the [google/mt5-base](https://huggingface.co/google/mt5-base) model, in which Ukrainian and 9% English words remain.
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This model has 252M parameters - 43% of the original size.
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Special thanks for the practical example and inspiration: [cointegrated ](https://huggingface.co/cointegrated)
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## Citing & Authors
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```
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@misc{Uaritm,
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title={SetFit: Classification of medical texts},
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author={Vitaliy Ostashko},
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year={2022},
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url={https://esemi.org},
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}
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```
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