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

eng-ine

  • source group: English

  • target group: Indo-European languages

  • OPUS readme: eng-ine

  • model: transformer

  • source language(s): eng

  • target 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

  • model: transformer

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

  • a sentence initial language token is required in the form of >>id<< (id = valid target language ID)

  • 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-enghin.eng.hin 6.2 0.317
newsdev2016-enro-engron.eng.ron 22.1 0.525
newsdev2017-enlv-englav.eng.lav 17.4 0.486
newsdev2019-engu-engguj.eng.guj 6.5 0.303
newsdev2019-enlt-englit.eng.lit 14.9 0.476
newsdiscussdev2015-enfr-engfra.eng.fra 26.4 0.547
newsdiscusstest2015-enfr-engfra.eng.fra 30.0 0.575
newssyscomb2009-engces.eng.ces 14.7 0.442
newssyscomb2009-engdeu.eng.deu 16.7 0.487
newssyscomb2009-engfra.eng.fra 24.8 0.547
newssyscomb2009-engita.eng.ita 25.2 0.562
newssyscomb2009-engspa.eng.spa 27.0 0.554
news-test2008-engces.eng.ces 13.0 0.417
news-test2008-engdeu.eng.deu 17.4 0.480
news-test2008-engfra.eng.fra 22.3 0.519
news-test2008-engspa.eng.spa 24.9 0.532
newstest2009-engces.eng.ces 13.6 0.432
newstest2009-engdeu.eng.deu 16.6 0.482
newstest2009-engfra.eng.fra 23.5 0.535
newstest2009-engita.eng.ita 25.5 0.561
newstest2009-engspa.eng.spa 26.3 0.551
newstest2010-engces.eng.ces 14.2 0.436
newstest2010-engdeu.eng.deu 18.3 0.492
newstest2010-engfra.eng.fra 25.7 0.550
newstest2010-engspa.eng.spa 30.5 0.578
newstest2011-engces.eng.ces 15.1 0.439
newstest2011-engdeu.eng.deu 17.1 0.478
newstest2011-engfra.eng.fra 28.0 0.569
newstest2011-engspa.eng.spa 31.9 0.580
newstest2012-engces.eng.ces 13.6 0.418
newstest2012-engdeu.eng.deu 17.0 0.475
newstest2012-engfra.eng.fra 26.1 0.553
newstest2012-engrus.eng.rus 21.4 0.506
newstest2012-engspa.eng.spa 31.4 0.577
newstest2013-engces.eng.ces 15.3 0.438
newstest2013-engdeu.eng.deu 20.3 0.501
newstest2013-engfra.eng.fra 26.0 0.540
newstest2013-engrus.eng.rus 16.1 0.449
newstest2013-engspa.eng.spa 28.6 0.555
newstest2014-hien-enghin.eng.hin 9.5 0.344
newstest2015-encs-engces.eng.ces 14.8 0.440
newstest2015-ende-engdeu.eng.deu 22.6 0.523
newstest2015-enru-engrus.eng.rus 18.8 0.483
newstest2016-encs-engces.eng.ces 16.8 0.457
newstest2016-ende-engdeu.eng.deu 26.2 0.555
newstest2016-enro-engron.eng.ron 21.2 0.510
newstest2016-enru-engrus.eng.rus 17.6 0.471
newstest2017-encs-engces.eng.ces 13.6 0.421
newstest2017-ende-engdeu.eng.deu 21.5 0.516
newstest2017-enlv-englav.eng.lav 13.0 0.452
newstest2017-enru-engrus.eng.rus 18.7 0.486
newstest2018-encs-engces.eng.ces 13.5 0.425
newstest2018-ende-engdeu.eng.deu 29.8 0.581
newstest2018-enru-engrus.eng.rus 16.1 0.472
newstest2019-encs-engces.eng.ces 14.8 0.435
newstest2019-ende-engdeu.eng.deu 26.6 0.554
newstest2019-engu-engguj.eng.guj 6.9 0.313
newstest2019-enlt-englit.eng.lit 10.6 0.429
newstest2019-enru-engrus.eng.rus 17.5 0.452
Tatoeba-test.eng-afr.eng.afr 52.1 0.708
Tatoeba-test.eng-ang.eng.ang 5.1 0.131
Tatoeba-test.eng-arg.eng.arg 1.2 0.099
Tatoeba-test.eng-asm.eng.asm 2.9 0.259
Tatoeba-test.eng-ast.eng.ast 14.1 0.408
Tatoeba-test.eng-awa.eng.awa 0.3 0.002
Tatoeba-test.eng-bel.eng.bel 18.1 0.450
Tatoeba-test.eng-ben.eng.ben 13.5 0.432
Tatoeba-test.eng-bho.eng.bho 0.3 0.003
Tatoeba-test.eng-bre.eng.bre 10.4 0.318
Tatoeba-test.eng-bul.eng.bul 38.7 0.592
Tatoeba-test.eng-cat.eng.cat 42.0 0.633
Tatoeba-test.eng-ces.eng.ces 32.3 0.546
Tatoeba-test.eng-cor.eng.cor 0.5 0.079
Tatoeba-test.eng-cos.eng.cos 3.1 0.148
Tatoeba-test.eng-csb.eng.csb 1.4 0.216
Tatoeba-test.eng-cym.eng.cym 22.4 0.470
Tatoeba-test.eng-dan.eng.dan 49.7 0.671
Tatoeba-test.eng-deu.eng.deu 31.7 0.554
Tatoeba-test.eng-dsb.eng.dsb 1.1 0.139
Tatoeba-test.eng-egl.eng.egl 0.9 0.089
Tatoeba-test.eng-ell.eng.ell 42.7 0.640
Tatoeba-test.eng-enm.eng.enm 3.5 0.259
Tatoeba-test.eng-ext.eng.ext 6.4 0.235
Tatoeba-test.eng-fao.eng.fao 6.6 0.285
Tatoeba-test.eng-fas.eng.fas 5.7 0.257
Tatoeba-test.eng-fra.eng.fra 38.4 0.595
Tatoeba-test.eng-frm.eng.frm 0.9 0.149
Tatoeba-test.eng-frr.eng.frr 8.4 0.145
Tatoeba-test.eng-fry.eng.fry 16.5 0.411
Tatoeba-test.eng-gcf.eng.gcf 0.6 0.098
Tatoeba-test.eng-gla.eng.gla 11.6 0.361
Tatoeba-test.eng-gle.eng.gle 32.5 0.546
Tatoeba-test.eng-glg.eng.glg 38.4 0.602
Tatoeba-test.eng-glv.eng.glv 23.1 0.418
Tatoeba-test.eng-gos.eng.gos 0.7 0.137
Tatoeba-test.eng-got.eng.got 0.2 0.010
Tatoeba-test.eng-grc.eng.grc 0.0 0.005
Tatoeba-test.eng-gsw.eng.gsw 0.9 0.108
Tatoeba-test.eng-guj.eng.guj 20.8 0.391
Tatoeba-test.eng-hat.eng.hat 34.0 0.537
Tatoeba-test.eng-hbs.eng.hbs 33.7 0.567
Tatoeba-test.eng-hif.eng.hif 2.8 0.269
Tatoeba-test.eng-hin.eng.hin 15.6 0.437
Tatoeba-test.eng-hsb.eng.hsb 5.4 0.320
Tatoeba-test.eng-hye.eng.hye 17.4 0.426
Tatoeba-test.eng-isl.eng.isl 17.4 0.436
Tatoeba-test.eng-ita.eng.ita 40.4 0.636
Tatoeba-test.eng-jdt.eng.jdt 6.4 0.008
Tatoeba-test.eng-kok.eng.kok 6.6 0.005
Tatoeba-test.eng-ksh.eng.ksh 0.8 0.123
Tatoeba-test.eng-kur.eng.kur 10.2 0.209
Tatoeba-test.eng-lad.eng.lad 0.8 0.163
Tatoeba-test.eng-lah.eng.lah 0.2 0.001
Tatoeba-test.eng-lat.eng.lat 9.4 0.372
Tatoeba-test.eng-lav.eng.lav 30.3 0.559
Tatoeba-test.eng-lij.eng.lij 1.0 0.130
Tatoeba-test.eng-lit.eng.lit 25.3 0.560
Tatoeba-test.eng-lld.eng.lld 0.4 0.139
Tatoeba-test.eng-lmo.eng.lmo 0.6 0.108
Tatoeba-test.eng-ltz.eng.ltz 18.1 0.388
Tatoeba-test.eng-mai.eng.mai 17.2 0.464
Tatoeba-test.eng-mar.eng.mar 18.0 0.451
Tatoeba-test.eng-mfe.eng.mfe 81.0 0.899
Tatoeba-test.eng-mkd.eng.mkd 37.6 0.587
Tatoeba-test.eng-msa.eng.msa 27.7 0.519
Tatoeba-test.eng.multi 32.6 0.539
Tatoeba-test.eng-mwl.eng.mwl 3.8 0.134
Tatoeba-test.eng-nds.eng.nds 14.3 0.401
Tatoeba-test.eng-nep.eng.nep 0.5 0.002
Tatoeba-test.eng-nld.eng.nld 44.0 0.642
Tatoeba-test.eng-non.eng.non 0.7 0.118
Tatoeba-test.eng-nor.eng.nor 42.7 0.623
Tatoeba-test.eng-oci.eng.oci 7.2 0.295
Tatoeba-test.eng-ori.eng.ori 2.7 0.257
Tatoeba-test.eng-orv.eng.orv 0.2 0.008
Tatoeba-test.eng-oss.eng.oss 2.9 0.264
Tatoeba-test.eng-pan.eng.pan 7.4 0.337
Tatoeba-test.eng-pap.eng.pap 48.5 0.656
Tatoeba-test.eng-pdc.eng.pdc 1.8 0.145
Tatoeba-test.eng-pms.eng.pms 0.7 0.136
Tatoeba-test.eng-pol.eng.pol 31.1 0.563
Tatoeba-test.eng-por.eng.por 37.0 0.605
Tatoeba-test.eng-prg.eng.prg 0.2 0.100
Tatoeba-test.eng-pus.eng.pus 1.0 0.134
Tatoeba-test.eng-roh.eng.roh 2.3 0.236
Tatoeba-test.eng-rom.eng.rom 7.8 0.340
Tatoeba-test.eng-ron.eng.ron 34.3 0.585
Tatoeba-test.eng-rue.eng.rue 0.2 0.010
Tatoeba-test.eng-rus.eng.rus 29.6 0.526
Tatoeba-test.eng-san.eng.san 2.4 0.125
Tatoeba-test.eng-scn.eng.scn 1.6 0.079
Tatoeba-test.eng-sco.eng.sco 33.6 0.562
Tatoeba-test.eng-sgs.eng.sgs 3.4 0.114
Tatoeba-test.eng-sin.eng.sin 9.2 0.349
Tatoeba-test.eng-slv.eng.slv 15.6 0.334
Tatoeba-test.eng-snd.eng.snd 9.1 0.324
Tatoeba-test.eng-spa.eng.spa 43.4 0.645
Tatoeba-test.eng-sqi.eng.sqi 39.0 0.621
Tatoeba-test.eng-stq.eng.stq 10.8 0.373
Tatoeba-test.eng-swe.eng.swe 49.9 0.663
Tatoeba-test.eng-swg.eng.swg 0.7 0.137
Tatoeba-test.eng-tgk.eng.tgk 6.4 0.346
Tatoeba-test.eng-tly.eng.tly 0.5 0.055
Tatoeba-test.eng-ukr.eng.ukr 31.4 0.536
Tatoeba-test.eng-urd.eng.urd 11.1 0.389
Tatoeba-test.eng-vec.eng.vec 1.3 0.110
Tatoeba-test.eng-wln.eng.wln 6.8 0.233
Tatoeba-test.eng-yid.eng.yid 5.8 0.295
Tatoeba-test.eng-zza.eng.zza 0.8 0.086

System Info:

  • hf_name: eng-ine

  • source_languages: eng

  • target_languages: ine

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

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['en', 'ca', 'es', 'os', 'ro', 'fy', 'cy', 'sc', 'is', 'yi', 'lb', 'an', 'sq', 'fr', 'ht', 'rm', 'ps', 'af', 'uk', 'sl', 'lt', 'bg', 'be', 'gd', 'si', '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: {'eng'}

  • tgt_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'}

  • src_multilingual: False

  • tgt_multilingual: True

  • prepro: normalization + SentencePiece (spm32k,spm32k)

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

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

  • src_alpha3: eng

  • tgt_alpha3: ine

  • short_pair: en-ine

  • chrF2_score: 0.539

  • bleu: 32.6

  • brevity_penalty: 0.973

  • ref_len: 68664.0

  • src_name: English

  • tgt_name: Indo-European languages

  • train_date: 2020-08-01

  • src_alpha2: en

  • tgt_alpha2: ine

  • prefer_old: False

  • long_pair: eng-ine

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41