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

  • source group: English

  • target group: Indic languages

  • OPUS readme: eng-inc

  • model: transformer

  • source language(s): eng

  • target language(s): asm awa ben bho gom guj hif_Latn hin mai mar npi ori pan_Guru pnb rom san_Deva sin snd_Arab urd

  • 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 8.2 0.342
newsdev2019-engu-engguj.eng.guj 6.5 0.293
newstest2014-hien-enghin.eng.hin 11.4 0.364
newstest2019-engu-engguj.eng.guj 7.2 0.296
Tatoeba-test.eng-asm.eng.asm 2.7 0.277
Tatoeba-test.eng-awa.eng.awa 0.5 0.132
Tatoeba-test.eng-ben.eng.ben 16.7 0.470
Tatoeba-test.eng-bho.eng.bho 4.3 0.227
Tatoeba-test.eng-guj.eng.guj 17.5 0.373
Tatoeba-test.eng-hif.eng.hif 0.6 0.028
Tatoeba-test.eng-hin.eng.hin 17.7 0.469
Tatoeba-test.eng-kok.eng.kok 1.7 0.000
Tatoeba-test.eng-lah.eng.lah 0.3 0.028
Tatoeba-test.eng-mai.eng.mai 15.6 0.429
Tatoeba-test.eng-mar.eng.mar 21.3 0.477
Tatoeba-test.eng.multi 17.3 0.448
Tatoeba-test.eng-nep.eng.nep 0.8 0.081
Tatoeba-test.eng-ori.eng.ori 2.2 0.208
Tatoeba-test.eng-pan.eng.pan 8.0 0.347
Tatoeba-test.eng-rom.eng.rom 0.4 0.197
Tatoeba-test.eng-san.eng.san 0.5 0.108
Tatoeba-test.eng-sin.eng.sin 9.1 0.364
Tatoeba-test.eng-snd.eng.snd 4.4 0.284
Tatoeba-test.eng-urd.eng.urd 13.3 0.423

System Info:

  • hf_name: eng-inc

  • source_languages: eng

  • target_languages: inc

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

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['en', 'bn', 'or', 'gu', 'mr', 'ur', 'hi', 'as', 'si', 'inc']

  • src_constituents: {'eng'}

  • tgt_constituents: {'pnb', 'gom', 'ben', 'hif_Latn', 'ori', 'guj', 'pan_Guru', 'snd_Arab', 'npi', 'mar', 'urd', 'bho', 'hin', 'san_Deva', 'asm', 'rom', 'mai', 'awa', 'sin'}

  • src_multilingual: False

  • tgt_multilingual: True

  • prepro: normalization + SentencePiece (spm32k,spm32k)

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

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

  • src_alpha3: eng

  • tgt_alpha3: inc

  • short_pair: en-inc

  • chrF2_score: 0.44799999999999995

  • bleu: 17.3

  • brevity_penalty: 1.0

  • ref_len: 59917.0

  • src_name: English

  • tgt_name: Indic languages

  • train_date: 2020-08-01

  • src_alpha2: en

  • tgt_alpha2: inc

  • prefer_old: False

  • long_pair: eng-inc

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41