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Helsinki-NLP/opus-mt-ine-en Helsinki-NLP/opus-mt-ine-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-ine-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ine-en")
Uploaded in S3

ine-eng

  • source group: Indo-European languages

  • target group: English

  • OPUS readme: ine-eng

  • model: transformer

  • source language(s): afr aln ang_Latn arg asm ast awa bel bel_Latn ben bho bos_Latn bre bul bul_Latn cat ces cor cos csb_Latn cym dan deu dsb egl ell enm_Latn ext fao fra frm_Latn frr fry gcf_Latn gla gle glg glv gom gos got_Goth grc_Grek gsw guj hat hif_Latn hin hrv hsb hye ind isl ita jdt_Cyrl ksh kur_Arab kur_Latn lad lad_Latn lat_Latn lav lij lit lld_Latn lmo ltg ltz mai mar max_Latn mfe min mkd mwl nds nld nno nob nob_Hebr non_Latn npi oci ori orv_Cyrl oss pan_Guru pap pdc pes pes_Latn pes_Thaa pms pnb pol por prg_Latn pus roh rom ron rue rus san_Deva scn sco sgs sin slv snd_Arab spa sqi srp_Cyrl srp_Latn stq swe swg tgk_Cyrl tly_Latn tmw_Latn ukr urd vec wln yid zlm_Latn zsm_Latn zza

  • 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
newsdev2014-hineng.hin.eng 11.2 0.375
newsdev2016-enro-roneng.ron.eng 35.5 0.614
newsdev2017-enlv-laveng.lav.eng 25.1 0.542
newsdev2019-engu-gujeng.guj.eng 16.0 0.420
newsdev2019-enlt-liteng.lit.eng 24.0 0.522
newsdiscussdev2015-enfr-fraeng.fra.eng 30.1 0.550
newsdiscusstest2015-enfr-fraeng.fra.eng 33.4 0.572
newssyscomb2009-ceseng.ces.eng 24.0 0.520
newssyscomb2009-deueng.deu.eng 25.7 0.526
newssyscomb2009-fraeng.fra.eng 27.9 0.550
newssyscomb2009-itaeng.ita.eng 31.4 0.574
newssyscomb2009-spaeng.spa.eng 28.3 0.555
news-test2008-deueng.deu.eng 24.0 0.515
news-test2008-fraeng.fra.eng 24.5 0.524
news-test2008-spaeng.spa.eng 25.5 0.533
newstest2009-ceseng.ces.eng 23.3 0.516
newstest2009-deueng.deu.eng 23.2 0.512
newstest2009-fraeng.fra.eng 27.3 0.545
newstest2009-itaeng.ita.eng 30.3 0.567
newstest2009-spaeng.spa.eng 27.9 0.549
newstest2010-ceseng.ces.eng 23.8 0.523
newstest2010-deueng.deu.eng 26.2 0.545
newstest2010-fraeng.fra.eng 28.6 0.562
newstest2010-spaeng.spa.eng 31.4 0.581
newstest2011-ceseng.ces.eng 24.2 0.521
newstest2011-deueng.deu.eng 23.9 0.522
newstest2011-fraeng.fra.eng 29.5 0.570
newstest2011-spaeng.spa.eng 30.3 0.570
newstest2012-ceseng.ces.eng 23.5 0.516
newstest2012-deueng.deu.eng 24.9 0.529
newstest2012-fraeng.fra.eng 30.0 0.568
newstest2012-ruseng.rus.eng 29.9 0.565
newstest2012-spaeng.spa.eng 33.3 0.593
newstest2013-ceseng.ces.eng 25.6 0.531
newstest2013-deueng.deu.eng 27.7 0.545
newstest2013-fraeng.fra.eng 30.0 0.561
newstest2013-ruseng.rus.eng 24.4 0.514
newstest2013-spaeng.spa.eng 30.8 0.577
newstest2014-csen-ceseng.ces.eng 27.7 0.558
newstest2014-deen-deueng.deu.eng 27.7 0.545
newstest2014-fren-fraeng.fra.eng 32.2 0.592
newstest2014-hien-hineng.hin.eng 16.7 0.450
newstest2014-ruen-ruseng.rus.eng 27.2 0.552
newstest2015-encs-ceseng.ces.eng 25.4 0.518
newstest2015-ende-deueng.deu.eng 28.8 0.552
newstest2015-enru-ruseng.rus.eng 25.6 0.527
newstest2016-encs-ceseng.ces.eng 27.0 0.540
newstest2016-ende-deueng.deu.eng 33.5 0.592
newstest2016-enro-roneng.ron.eng 32.8 0.591
newstest2016-enru-ruseng.rus.eng 24.8 0.523
newstest2017-encs-ceseng.ces.eng 23.7 0.510
newstest2017-ende-deueng.deu.eng 29.3 0.556
newstest2017-enlv-laveng.lav.eng 18.9 0.486
newstest2017-enru-ruseng.rus.eng 28.0 0.546
newstest2018-encs-ceseng.ces.eng 24.9 0.521
newstest2018-ende-deueng.deu.eng 36.0 0.604
newstest2018-enru-ruseng.rus.eng 23.8 0.517
newstest2019-deen-deueng.deu.eng 31.5 0.570
newstest2019-guen-gujeng.guj.eng 12.1 0.377
newstest2019-lten-liteng.lit.eng 26.6 0.555
newstest2019-ruen-ruseng.rus.eng 27.5 0.541
Tatoeba-test.afr-eng.afr.eng 59.0 0.724
Tatoeba-test.ang-eng.ang.eng 9.9 0.254
Tatoeba-test.arg-eng.arg.eng 41.6 0.487
Tatoeba-test.asm-eng.asm.eng 22.8 0.392
Tatoeba-test.ast-eng.ast.eng 36.1 0.521
Tatoeba-test.awa-eng.awa.eng 11.6 0.280
Tatoeba-test.bel-eng.bel.eng 42.2 0.597
Tatoeba-test.ben-eng.ben.eng 45.8 0.598
Tatoeba-test.bho-eng.bho.eng 34.4 0.518
Tatoeba-test.bre-eng.bre.eng 24.4 0.405
Tatoeba-test.bul-eng.bul.eng 50.8 0.660
Tatoeba-test.cat-eng.cat.eng 51.2 0.677
Tatoeba-test.ces-eng.ces.eng 47.6 0.641
Tatoeba-test.cor-eng.cor.eng 5.4 0.214
Tatoeba-test.cos-eng.cos.eng 61.0 0.675
Tatoeba-test.csb-eng.csb.eng 22.5 0.394
Tatoeba-test.cym-eng.cym.eng 34.7 0.522
Tatoeba-test.dan-eng.dan.eng 56.2 0.708
Tatoeba-test.deu-eng.deu.eng 44.9 0.625
Tatoeba-test.dsb-eng.dsb.eng 21.0 0.383
Tatoeba-test.egl-eng.egl.eng 6.9 0.221
Tatoeba-test.ell-eng.ell.eng 62.1 0.741
Tatoeba-test.enm-eng.enm.eng 22.6 0.466
Tatoeba-test.ext-eng.ext.eng 33.2 0.496
Tatoeba-test.fao-eng.fao.eng 28.1 0.460
Tatoeba-test.fas-eng.fas.eng 9.6 0.306
Tatoeba-test.fra-eng.fra.eng 50.3 0.661
Tatoeba-test.frm-eng.frm.eng 30.0 0.457
Tatoeba-test.frr-eng.frr.eng 15.2 0.301
Tatoeba-test.fry-eng.fry.eng 34.4 0.525
Tatoeba-test.gcf-eng.gcf.eng 18.4 0.317
Tatoeba-test.gla-eng.gla.eng 24.1 0.400
Tatoeba-test.gle-eng.gle.eng 52.2 0.671
Tatoeba-test.glg-eng.glg.eng 50.5 0.669
Tatoeba-test.glv-eng.glv.eng 5.7 0.189
Tatoeba-test.gos-eng.gos.eng 19.2 0.378
Tatoeba-test.got-eng.got.eng 0.1 0.022
Tatoeba-test.grc-eng.grc.eng 0.9 0.095
Tatoeba-test.gsw-eng.gsw.eng 23.9 0.390
Tatoeba-test.guj-eng.guj.eng 28.0 0.428
Tatoeba-test.hat-eng.hat.eng 44.2 0.567
Tatoeba-test.hbs-eng.hbs.eng 51.6 0.666
Tatoeba-test.hif-eng.hif.eng 22.3 0.451
Tatoeba-test.hin-eng.hin.eng 41.7 0.585
Tatoeba-test.hsb-eng.hsb.eng 46.4 0.590
Tatoeba-test.hye-eng.hye.eng 40.4 0.564
Tatoeba-test.isl-eng.isl.eng 43.8 0.605
Tatoeba-test.ita-eng.ita.eng 60.7 0.735
Tatoeba-test.jdt-eng.jdt.eng 5.5 0.091
Tatoeba-test.kok-eng.kok.eng 7.8 0.205
Tatoeba-test.ksh-eng.ksh.eng 15.8 0.284
Tatoeba-test.kur-eng.kur.eng 11.6 0.232
Tatoeba-test.lad-eng.lad.eng 30.7 0.484
Tatoeba-test.lah-eng.lah.eng 11.0 0.286
Tatoeba-test.lat-eng.lat.eng 24.4 0.432
Tatoeba-test.lav-eng.lav.eng 47.2 0.646
Tatoeba-test.lij-eng.lij.eng 9.0 0.287
Tatoeba-test.lit-eng.lit.eng 51.7 0.670
Tatoeba-test.lld-eng.lld.eng 22.4 0.369
Tatoeba-test.lmo-eng.lmo.eng 26.1 0.381
Tatoeba-test.ltz-eng.ltz.eng 39.8 0.536
Tatoeba-test.mai-eng.mai.eng 72.3 0.758
Tatoeba-test.mar-eng.mar.eng 32.0 0.554
Tatoeba-test.mfe-eng.mfe.eng 63.1 0.822
Tatoeba-test.mkd-eng.mkd.eng 49.5 0.638
Tatoeba-test.msa-eng.msa.eng 38.6 0.566
Tatoeba-test.multi.eng 45.6 0.615
Tatoeba-test.mwl-eng.mwl.eng 40.4 0.767
Tatoeba-test.nds-eng.nds.eng 35.5 0.538
Tatoeba-test.nep-eng.nep.eng 4.9 0.209
Tatoeba-test.nld-eng.nld.eng 54.2 0.694
Tatoeba-test.non-eng.non.eng 39.3 0.573
Tatoeba-test.nor-eng.nor.eng 50.9 0.663
Tatoeba-test.oci-eng.oci.eng 19.6 0.386
Tatoeba-test.ori-eng.ori.eng 16.2 0.364
Tatoeba-test.orv-eng.orv.eng 13.6 0.288
Tatoeba-test.oss-eng.oss.eng 9.4 0.301
Tatoeba-test.pan-eng.pan.eng 17.1 0.389
Tatoeba-test.pap-eng.pap.eng 57.0 0.680
Tatoeba-test.pdc-eng.pdc.eng 41.6 0.526
Tatoeba-test.pms-eng.pms.eng 13.7 0.333
Tatoeba-test.pol-eng.pol.eng 46.5 0.632
Tatoeba-test.por-eng.por.eng 56.4 0.710
Tatoeba-test.prg-eng.prg.eng 2.3 0.193
Tatoeba-test.pus-eng.pus.eng 3.2 0.194
Tatoeba-test.roh-eng.roh.eng 17.5 0.420
Tatoeba-test.rom-eng.rom.eng 5.0 0.237
Tatoeba-test.ron-eng.ron.eng 51.4 0.670
Tatoeba-test.rue-eng.rue.eng 26.0 0.447
Tatoeba-test.rus-eng.rus.eng 47.8 0.634
Tatoeba-test.san-eng.san.eng 4.0 0.195
Tatoeba-test.scn-eng.scn.eng 45.1 0.440
Tatoeba-test.sco-eng.sco.eng 41.9 0.582
Tatoeba-test.sgs-eng.sgs.eng 38.7 0.498
Tatoeba-test.sin-eng.sin.eng 29.7 0.499
Tatoeba-test.slv-eng.slv.eng 38.2 0.564
Tatoeba-test.snd-eng.snd.eng 12.7 0.342
Tatoeba-test.spa-eng.spa.eng 53.2 0.687
Tatoeba-test.sqi-eng.sqi.eng 51.9 0.679
Tatoeba-test.stq-eng.stq.eng 9.0 0.391
Tatoeba-test.swe-eng.swe.eng 57.4 0.705
Tatoeba-test.swg-eng.swg.eng 18.0 0.338
Tatoeba-test.tgk-eng.tgk.eng 24.3 0.413
Tatoeba-test.tly-eng.tly.eng 1.1 0.094
Tatoeba-test.ukr-eng.ukr.eng 48.0 0.639
Tatoeba-test.urd-eng.urd.eng 27.2 0.471
Tatoeba-test.vec-eng.vec.eng 28.0 0.398
Tatoeba-test.wln-eng.wln.eng 17.5 0.320
Tatoeba-test.yid-eng.yid.eng 26.9 0.457
Tatoeba-test.zza-eng.zza.eng 1.7 0.131

System Info:

  • hf_name: ine-eng

  • source_languages: ine

  • target_languages: eng

  • opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ine-eng/README.md

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['ca', 'es', 'os', 'ro', 'fy', 'cy', 'sc', 'is', 'yi', 'lb', 'an', 'sq', 'fr', 'ht', 'rm', 'ps', 'af', 'uk', 'sl', 'lt', 'bg', 'be', 'gd', 'si', 'en', 'br', 'mk', 'or', 'mr', 'ru', 'fo', 'co', 'oc', 'pl', 'gl', 'nb', 'bn', 'id', 'hy', 'da', 'gv', 'nl', 'pt', 'hi', 'as', 'kw', 'ga', 'sv', 'gu', 'wa', 'lv', 'el', 'it', 'hr', 'ur', 'nn', 'de', 'cs', 'ine']

  • src_constituents: {'cat', 'spa', 'pap', 'mwl', 'lij', 'bos_Latn', 'lad_Latn', 'lat_Latn', 'pcd', 'oss', 'ron', 'fry', 'cym', 'awa', 'swg', 'zsm_Latn', 'srd', 'gcf_Latn', 'isl', 'yid', 'bho', 'ltz', 'kur_Latn', 'arg', 'pes_Thaa', 'sqi', 'csb_Latn', 'fra', 'hat', 'non_Latn', 'sco', 'pnb', 'roh', 'bul_Latn', 'pus', 'afr', 'ukr', 'slv', 'lit', 'tmw_Latn', 'hsb', 'tly_Latn', 'bul', 'bel', 'got_Goth', 'lat_Grek', 'ext', 'gla', 'mai', 'sin', 'hif_Latn', 'eng', 'bre', 'nob_Hebr', 'prg_Latn', 'ang_Latn', 'aln', 'mkd', 'ori', 'mar', 'afr_Arab', 'san_Deva', 'gos', 'rus', 'fao', 'orv_Cyrl', 'bel_Latn', 'cos', 'zza', 'grc_Grek', 'oci', 'mfe', 'gom', 'bjn', 'sgs', 'tgk_Cyrl', 'hye_Latn', 'pdc', 'srp_Cyrl', 'pol', 'ast', 'glg', 'pms', 'nob', 'ben', 'min', 'srp_Latn', 'zlm_Latn', 'ind', 'rom', 'hye', 'scn', 'enm_Latn', 'lmo', 'npi', 'pes', 'dan', 'rus_Latn', 'jdt_Cyrl', 'gsw', 'glv', 'nld', 'snd_Arab', 'kur_Arab', 'por', 'hin', 'dsb', 'asm', 'lad', 'frm_Latn', 'ksh', 'pan_Guru', 'cor', 'gle', 'swe', 'guj', 'wln', 'lav', 'ell', 'frr', 'rue', 'ita', 'hrv', 'urd', 'stq', 'nno', 'deu', 'lld_Latn', 'ces', 'egl', 'vec', 'max_Latn', 'pes_Latn', 'ltg', 'nds'}

  • tgt_constituents: {'eng'}

  • src_multilingual: True

  • tgt_multilingual: False

  • prepro: normalization + SentencePiece (spm32k,spm32k)

  • url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus2m-2020-08-01.zip

  • url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus2m-2020-08-01.test.txt

  • src_alpha3: ine

  • tgt_alpha3: eng

  • short_pair: ine-en

  • chrF2_score: 0.615

  • bleu: 45.6

  • brevity_penalty: 0.997

  • ref_len: 71872.0

  • src_name: Indo-European languages

  • tgt_name: English

  • train_date: 2020-08-01

  • src_alpha2: ine

  • tgt_alpha2: en

  • prefer_old: False

  • long_pair: ine-eng

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41