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Helsinki-NLP/opus-mt-gmw-en Helsinki-NLP/opus-mt-gmw-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-gmw-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-gmw-en")
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gmw-eng

  • source group: West Germanic languages

  • target group: English

  • OPUS readme: gmw-eng

  • model: transformer

  • source language(s): afr ang_Latn deu enm_Latn frr fry gos gsw ksh ltz nds nld pdc sco stq swg yid

  • target language(s): eng

  • model: transformer

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

  • download original weights: opus2m-2020-08-01.zip

  • test set translations: opus2m-2020-08-01.test.txt

  • test set scores: opus2m-2020-08-01.eval.txt

Benchmarks

testset BLEU chr-F
newssyscomb2009-deueng.deu.eng 27.2 0.538
news-test2008-deueng.deu.eng 25.7 0.534
newstest2009-deueng.deu.eng 25.1 0.530
newstest2010-deueng.deu.eng 27.9 0.565
newstest2011-deueng.deu.eng 25.3 0.539
newstest2012-deueng.deu.eng 26.6 0.548
newstest2013-deueng.deu.eng 29.6 0.565
newstest2014-deen-deueng.deu.eng 30.2 0.571
newstest2015-ende-deueng.deu.eng 31.5 0.577
newstest2016-ende-deueng.deu.eng 36.7 0.622
newstest2017-ende-deueng.deu.eng 32.3 0.585
newstest2018-ende-deueng.deu.eng 39.9 0.638
newstest2019-deen-deueng.deu.eng 35.9 0.611
Tatoeba-test.afr-eng.afr.eng 61.8 0.750
Tatoeba-test.ang-eng.ang.eng 7.3 0.220
Tatoeba-test.deu-eng.deu.eng 48.3 0.657
Tatoeba-test.enm-eng.enm.eng 16.1 0.423
Tatoeba-test.frr-eng.frr.eng 7.0 0.168
Tatoeba-test.fry-eng.fry.eng 28.6 0.488
Tatoeba-test.gos-eng.gos.eng 15.5 0.326
Tatoeba-test.gsw-eng.gsw.eng 12.7 0.308
Tatoeba-test.ksh-eng.ksh.eng 8.4 0.254
Tatoeba-test.ltz-eng.ltz.eng 28.7 0.453
Tatoeba-test.multi.eng 48.5 0.646
Tatoeba-test.nds-eng.nds.eng 31.4 0.509
Tatoeba-test.nld-eng.nld.eng 58.1 0.728
Tatoeba-test.pdc-eng.pdc.eng 25.1 0.406
Tatoeba-test.sco-eng.sco.eng 40.8 0.570
Tatoeba-test.stq-eng.stq.eng 20.3 0.380
Tatoeba-test.swg-eng.swg.eng 20.5 0.315
Tatoeba-test.yid-eng.yid.eng 16.0 0.366

System Info: