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https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-trk
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Helsinki-NLP/opus-mt-en-trk Helsinki-NLP/opus-mt-en-trk
238 downloads
last 30 days

pytorch

tf

Contributed by

Language Technology Research Group at the University of Helsinki university
1 team member · 1323 models

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

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

  • source group: English

  • target group: Turkic languages

  • OPUS readme: eng-trk

  • model: transformer

  • source language(s): eng

  • target language(s): aze_Latn bak chv crh crh_Latn kaz_Cyrl kaz_Latn kir_Cyrl kjh kum ota_Arab ota_Latn sah tat tat_Arab tat_Latn tuk tuk_Latn tur tyv uig_Arab uig_Cyrl uzb_Cyrl uzb_Latn

  • 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
newsdev2016-entr-engtur.eng.tur 10.1 0.437
newstest2016-entr-engtur.eng.tur 9.2 0.410
newstest2017-entr-engtur.eng.tur 9.0 0.410
newstest2018-entr-engtur.eng.tur 9.2 0.413
Tatoeba-test.eng-aze.eng.aze 26.8 0.577
Tatoeba-test.eng-bak.eng.bak 7.6 0.308
Tatoeba-test.eng-chv.eng.chv 4.3 0.270
Tatoeba-test.eng-crh.eng.crh 8.1 0.330
Tatoeba-test.eng-kaz.eng.kaz 11.1 0.359
Tatoeba-test.eng-kir.eng.kir 28.6 0.524
Tatoeba-test.eng-kjh.eng.kjh 1.0 0.041
Tatoeba-test.eng-kum.eng.kum 2.2 0.075
Tatoeba-test.eng.multi 19.9 0.455
Tatoeba-test.eng-ota.eng.ota 0.5 0.065
Tatoeba-test.eng-sah.eng.sah 0.7 0.030
Tatoeba-test.eng-tat.eng.tat 9.7 0.316
Tatoeba-test.eng-tuk.eng.tuk 5.9 0.317
Tatoeba-test.eng-tur.eng.tur 34.6 0.623
Tatoeba-test.eng-tyv.eng.tyv 5.4 0.210
Tatoeba-test.eng-uig.eng.uig 0.1 0.155
Tatoeba-test.eng-uzb.eng.uzb 3.4 0.275

System Info:

  • hf_name: eng-trk

  • source_languages: eng

  • target_languages: trk

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

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['en', 'tt', 'cv', 'tk', 'tr', 'ba', 'trk']

  • src_constituents: {'eng'}

  • tgt_constituents: {'kir_Cyrl', 'tat_Latn', 'tat', 'chv', 'uzb_Cyrl', 'kaz_Latn', 'aze_Latn', 'crh', 'kjh', 'uzb_Latn', 'ota_Arab', 'tuk_Latn', 'tuk', 'tat_Arab', 'sah', 'tyv', 'tur', 'uig_Arab', 'crh_Latn', 'kaz_Cyrl', 'uig_Cyrl', 'kum', 'ota_Latn', 'bak'}

  • src_multilingual: False

  • tgt_multilingual: True

  • prepro: normalization + SentencePiece (spm32k,spm32k)

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

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

  • src_alpha3: eng

  • tgt_alpha3: trk

  • short_pair: en-trk

  • chrF2_score: 0.455

  • bleu: 19.9

  • brevity_penalty: 1.0

  • ref_len: 57072.0

  • src_name: English

  • tgt_name: Turkic languages

  • train_date: 2020-08-01

  • src_alpha2: en

  • tgt_alpha2: trk

  • prefer_old: False

  • long_pair: eng-trk

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41