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# MTee translation model for
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The model uses a modular architecture, where each language has its own encoder and decoder that is used for all translation directions. The model can be used with our custom version of [FairSeq](https://github.com/TartuNLP/fairseq) and it is compatible with the [MTee](https://github.com/Project-MTee) platform and its [NMT workers](https://github.com/Project-MTee/translation-worker). Additionally, it is fully compatible with TartuNLP's translation API components ([API](https://github.com/TartuNLP/translation-api) and [NMT workers](https://github.com/TartuNLP/translation-worker)).
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# MTee translation model for legal domain
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A legal domain translation model for the MTee machine translation platform. The platform was developed in 2021 as a collaboration between the [TartuNLP](https://tartunlp.ai), the NLP research group at the University of Tartu, and [Tilde](https://tilde.com). More information about the project can be found [here](https://github.com/Project-MTee/mtee-platform/wiki).
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The model uses a modular architecture, where each language has its own encoder and decoder that is used for all translation directions. The model can be used with our custom version of [FairSeq](https://github.com/TartuNLP/fairseq) and it is compatible with the [MTee](https://github.com/Project-MTee) platform and its [NMT workers](https://github.com/Project-MTee/translation-worker). Additionally, it is fully compatible with TartuNLP's translation API components ([API](https://github.com/TartuNLP/translation-api) and [NMT workers](https://github.com/TartuNLP/translation-worker)).
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