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Helsinki-NLP/opus-mt-gmq-en Helsinki-NLP/opus-mt-gmq-en
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last 30 days

pytorch

tf

Contributed by

Language Technology Research Group at the University of Helsinki university
1 team member · 1325 models

How to use this model directly from the 🤗/transformers library:

			
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-gmq-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-gmq-en")
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gmq-eng

  • source group: North Germanic languages

  • target group: English

  • OPUS readme: gmq-eng

  • model: transformer

  • source language(s): dan fao isl nno nob nob_Hebr non_Latn swe

  • target language(s): eng

  • model: transformer

  • pre-processing: normalization + SentencePiece (spm32k,spm32k)

  • download original weights: opus2m-2020-07-26.zip

  • test set translations: opus2m-2020-07-26.test.txt

  • test set scores: opus2m-2020-07-26.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.multi.eng 58.1 0.720

System Info: