This is a COMET evaluation model: It receives a triplet with (source sentence, translation, reference translation) and returns a score that reflects the quality of the translation compared to both source and reference. Paper COMET 22: Unbabel IST 2022 Submission for the Metrics Shared Task (Rei et al., WMT 2022) License Apache 2.0 Usage (unbabel comet) Using this model requires unbabel comet to be installed: Then you can use it through comet CLI: Or using Python: Intended uses Our model is intented to be used for MT evaluation . Given a a triplet with (source sentence, translation, reference translation) outputs a single score between 0 and 1 where 1 represents a perfect translation. Languages Covered: This model builds on top of XLM R which cover the following languages: Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Azerbaijani, Basque, Belarusian, Bengali, Bengali Romanized, Bosnian, Breton, Bulgarian, Burmese, Burmese, Catalan, Chinese (Simplified), Chinese (Traditional), Croatian, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Hausa, Hebrew, Hindi, Hindi Romanized, Hungarian, Icelandic, Ind…
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