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README.md

@@ -0,0 +1,1085 @@
+---
+library_name: transformers
+language:
+- aa
+- am
+- ar
+- arc
+- bcw
+- byn
+- cop
+- daa
+- de
+- dsh
+- en
+- es
+- fr
+- gde
+- gnd
+- ha
+- hbo
+- he
+- hig
+- irk
+- jpa
+- kab
+- ker
+- kqp
+- ktb
+- kxc
+- lln
+- lme
+- meq
+- mfh
+- mfi
+- mfk
+- mif
+- mpg
+- mqb
+- mt
+- muy
+- oar
+- om
+- pbi
+- phn
+- pt
+- rif
+- sgw
+- shi
+- shy
+- so
+- sur
+- syc
+- syr
+- taq
+- thv
+- ti
+- tig
+- tmc
+- tmh
+- tmr
+- ttr
+- tzm
+- wal
+- xed
+- zgh
+
+tags:
+- translation
+- opus-mt-tc-bible
+
+license: apache-2.0
+model-index:
+- name: opus-mt-tc-bible-big-deu_eng_fra_por_spa-afa
+  results:
+  - task:
+      name: Translation deu-hau
+      type: translation
+      args: deu-hau
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: deu-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 11.4
+       - name: chr-F
+         type: chrf
+         value: 0.40471
+  - task:
+      name: Translation deu-heb
+      type: translation
+      args: deu-heb
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: deu-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.1
+       - name: chr-F
+         type: chrf
+         value: 0.48645
+  - task:
+      name: Translation deu-mlt
+      type: translation
+      args: deu-mlt
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: deu-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 17.5
+       - name: chr-F
+         type: chrf
+         value: 0.54079
+  - task:
+      name: Translation eng-arz
+      type: translation
+      args: eng-arz
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-arz
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 11.1
+       - name: chr-F
+         type: chrf
+         value: 0.42804
+  - task:
+      name: Translation eng-hau
+      type: translation
+      args: eng-hau
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 20.4
+       - name: chr-F
+         type: chrf
+         value: 0.49023
+  - task:
+      name: Translation eng-heb
+      type: translation
+      args: eng-heb
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 27.1
+       - name: chr-F
+         type: chrf
+         value: 0.56635
+  - task:
+      name: Translation eng-mlt
+      type: translation
+      args: eng-mlt
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 34.9
+       - name: chr-F
+         type: chrf
+         value: 0.68334
+  - task:
+      name: Translation fra-hau
+      type: translation
+      args: fra-hau
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: fra-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.2
+       - name: chr-F
+         type: chrf
+         value: 0.42731
+  - task:
+      name: Translation fra-heb
+      type: translation
+      args: fra-heb
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: fra-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 19.1
+       - name: chr-F
+         type: chrf
+         value: 0.49683
+  - task:
+      name: Translation fra-mlt
+      type: translation
+      args: fra-mlt
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: fra-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 20.4
+       - name: chr-F
+         type: chrf
+         value: 0.56844
+  - task:
+      name: Translation por-hau
+      type: translation
+      args: por-hau
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: por-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.6
+       - name: chr-F
+         type: chrf
+         value: 0.42593
+  - task:
+      name: Translation por-heb
+      type: translation
+      args: por-heb
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: por-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 19.7
+       - name: chr-F
+         type: chrf
+         value: 0.50345
+  - task:
+      name: Translation por-mlt
+      type: translation
+      args: por-mlt
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: por-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.5
+       - name: chr-F
+         type: chrf
+         value: 0.58913
+  - task:
+      name: Translation spa-heb
+      type: translation
+      args: spa-heb
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: spa-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.5
+       - name: chr-F
+         type: chrf
+         value: 0.45249
+  - task:
+      name: Translation spa-mlt
+      type: translation
+      args: spa-mlt
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: spa-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 12.7
+       - name: chr-F
+         type: chrf
+         value: 0.51077
+  - task:
+      name: Translation deu-ara
+      type: translation
+      args: deu-ara
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: deu ara devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 15.7
+       - name: chr-F
+         type: chrf
+         value: 0.47927
+  - task:
+      name: Translation deu-hau
+      type: translation
+      args: deu-hau
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: deu hau devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 10.6
+       - name: chr-F
+         type: chrf
+         value: 0.39583
+  - task:
+      name: Translation eng-hau
+      type: translation
+      args: eng-hau
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng hau devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 19.0
+       - name: chr-F
+         type: chrf
+         value: 0.47807
+  - task:
+      name: Translation eng-mlt
+      type: translation
+      args: eng-mlt
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng mlt devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.9
+       - name: chr-F
+         type: chrf
+         value: 0.67196
+  - task:
+      name: Translation fra-mlt
+      type: translation
+      args: fra-mlt
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: fra mlt devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 19.9
+       - name: chr-F
+         type: chrf
+         value: 0.56271
+  - task:
+      name: Translation por-heb
+      type: translation
+      args: por-heb
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: por heb devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 19.6
+       - name: chr-F
+         type: chrf
+         value: 0.49378
+  - task:
+      name: Translation spa-ara
+      type: translation
+      args: spa-ara
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: spa ara devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 11.7
+       - name: chr-F
+         type: chrf
+         value: 0.44988
+  - task:
+      name: Translation deu-hau
+      type: translation
+      args: deu-hau
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: deu-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 12.5
+       - name: chr-F
+         type: chrf
+         value: 0.41931
+  - task:
+      name: Translation deu-heb
+      type: translation
+      args: deu-heb
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: deu-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.3
+       - name: chr-F
+         type: chrf
+         value: 0.43961
+  - task:
+      name: Translation deu-mlt
+      type: translation
+      args: deu-mlt
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: deu-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 15.1
+       - name: chr-F
+         type: chrf
+         value: 0.49871
+  - task:
+      name: Translation eng-hau
+      type: translation
+      args: eng-hau
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: eng-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.2
+       - name: chr-F
+         type: chrf
+         value: 0.51601
+  - task:
+      name: Translation eng-heb
+      type: translation
+      args: eng-heb
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: eng-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 20.3
+       - name: chr-F
+         type: chrf
+         value: 0.50625
+  - task:
+      name: Translation eng-mlt
+      type: translation
+      args: eng-mlt
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: eng-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 29.0
+       - name: chr-F
+         type: chrf
+         value: 0.62552
+  - task:
+      name: Translation eng-som
+      type: translation
+      args: eng-som
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: eng-som
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.5
+       - name: chr-F
+         type: chrf
+         value: 0.46845
+  - task:
+      name: Translation fra-hau
+      type: translation
+      args: fra-hau
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: fra-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 14.5
+       - name: chr-F
+         type: chrf
+         value: 0.43729
+  - task:
+      name: Translation fra-heb
+      type: translation
+      args: fra-heb
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: fra-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.9
+       - name: chr-F
+         type: chrf
+         value: 0.43855
+  - task:
+      name: Translation fra-mlt
+      type: translation
+      args: fra-mlt
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: fra-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 17.3
+       - name: chr-F
+         type: chrf
+         value: 0.51640
+  - task:
+      name: Translation por-hau
+      type: translation
+      args: por-hau
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: por-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 15.1
+       - name: chr-F
+         type: chrf
+         value: 0.44408
+  - task:
+      name: Translation por-heb
+      type: translation
+      args: por-heb
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: por-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 15.0
+       - name: chr-F
+         type: chrf
+         value: 0.45739
+  - task:
+      name: Translation por-mlt
+      type: translation
+      args: por-mlt
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: por-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.2
+       - name: chr-F
+         type: chrf
+         value: 0.53719
+  - task:
+      name: Translation spa-hau
+      type: translation
+      args: spa-hau
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: spa-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 14.8
+       - name: chr-F
+         type: chrf
+         value: 0.44695
+  - task:
+      name: Translation spa-heb
+      type: translation
+      args: spa-heb
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: spa-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 14.5
+       - name: chr-F
+         type: chrf
+         value: 0.45509
+  - task:
+      name: Translation spa-mlt
+      type: translation
+      args: spa-mlt
+    dataset:
+      name: ntrex128
+      type: ntrex128
+      args: spa-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 17.7
+       - name: chr-F
+         type: chrf
+         value: 0.53631
+  - task:
+      name: Translation deu-ara
+      type: translation
+      args: deu-ara
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: deu-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 20.2
+       - name: chr-F
+         type: chrf
+         value: 0.49517
+  - task:
+      name: Translation deu-heb
+      type: translation
+      args: deu-heb
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: deu-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 35.8
+       - name: chr-F
+         type: chrf
+         value: 0.56943
+  - task:
+      name: Translation eng-heb
+      type: translation
+      args: eng-heb
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 34.9
+       - name: chr-F
+         type: chrf
+         value: 0.57708
+  - task:
+      name: Translation eng-mlt
+      type: translation
+      args: eng-mlt
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-mlt
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 29.5
+       - name: chr-F
+         type: chrf
+         value: 0.61044
+  - task:
+      name: Translation fra-heb
+      type: translation
+      args: fra-heb
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: fra-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 37.5
+       - name: chr-F
+         type: chrf
+         value: 0.58681
+  - task:
+      name: Translation por-heb
+      type: translation
+      args: por-heb
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: por-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 41.0
+       - name: chr-F
+         type: chrf
+         value: 0.61593
+  - task:
+      name: Translation spa-ara
+      type: translation
+      args: spa-ara
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: spa-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.9
+       - name: chr-F
+         type: chrf
+         value: 0.53669
+  - task:
+      name: Translation spa-heb
+      type: translation
+      args: spa-heb
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: spa-heb
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 41.2
+       - name: chr-F
+         type: chrf
+         value: 0.61966
+  - task:
+      name: Translation eng-ara
+      type: translation
+      args: eng-ara
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: eng-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.4
+       - name: chr-F
+         type: chrf
+         value: 0.56288
+  - task:
+      name: Translation eng-hau
+      type: translation
+      args: eng-hau
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: eng-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.2
+       - name: chr-F
+         type: chrf
+         value: 0.50060
+  - task:
+      name: Translation fra-ara
+      type: translation
+      args: fra-ara
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: fra-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.8
+       - name: chr-F
+         type: chrf
+         value: 0.39785
+  - task:
+      name: Translation por-ara
+      type: translation
+      args: por-ara
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: por-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 16.0
+       - name: chr-F
+         type: chrf
+         value: 0.44442
+  - task:
+      name: Translation spa-ara
+      type: translation
+      args: spa-ara
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: spa-ara
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 16.5
+       - name: chr-F
+         type: chrf
+         value: 0.45429
+  - task:
+      name: Translation eng-hau
+      type: translation
+      args: eng-hau
+    dataset:
+      name: newstest2021
+      type: wmt-2021-news
+      args: eng-hau
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 13.1
+       - name: chr-F
+         type: chrf
+         value: 0.43617
+---
+# opus-mt-tc-bible-big-deu_eng_fra_por_spa-afa
+
+## Table of Contents
+- [Model Details](#model-details)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation Information](#citation-information)
+- [Acknowledgements](#acknowledgements)
+
+## Model Details
+
+Neural machine translation model for translating from unknown (deu+eng+fra+por+spa) to Afro-Asiatic languages (afa).
+
+This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
+**Model Description:**
+- **Developed by:** Language Technology Research Group at the University of Helsinki
+- **Model Type:** Translation (transformer-big)
+- **Release**: 2024-05-29
+- **License:** Apache-2.0
+- **Language(s):**  
+  - Source Language(s): deu eng fra por spa
+  - Target Language(s): aar acm afb amh apc ara arc arq arz bcw byn cop daa dsh gde gnd hau hbo heb hig irk jpa kab ker kqp ktb kxc lln lme meq mfh mfi mfk mif mlt mpg mqb muy oar orm pbi phn rif sgw shi shy som sur syc syr taq thv tig tir tmc tmh tmr ttr tzm wal xed zgh
+  - Valid Target Language Labels: >>aal<< >>aar<< >>aas<< >>acm<< >>afb<< >>agj<< >>ahg<< >>aij<< >>aiw<< >>ajw<< >>akk<< >>alw<< >>amh<< >>amw<< >>anc<< >>ank<< >>apc<< >>ara<< >>arc<< >>arq<< >>arv<< >>arz<< >>auj<< >>auo<< >>awn<< >>bbt<< >>bcq<< >>bcw<< >>bcy<< >>bde<< >>bdm<< >>bdn<< >>bds<< >>bej<< >>bhm<< >>bhn<< >>bhs<< >>bid<< >>bjf<< >>bji<< >>bnl<< >>bob<< >>bol<< >>bsw<< >>bta<< >>btf<< >>bux<< >>bva<< >>bvf<< >>bvh<< >>bvw<< >>bwo<< >>bwr<< >>bxe<< >>bxq<< >>byn<< >>cie<< >>ckl<< >>ckq<< >>cky<< >>cla<< >>cnu<< >>cop<< >>cop_Copt<< >>cuv<< >>daa<< >>dal<< >>dbb<< >>dbp<< >>dbq<< >>dbr<< >>dgh<< >>dim<< >>dkx<< >>dlk<< >>dme<< >>dot<< >>dox<< >>doz<< >>drs<< >>dsh<< >>dwa<< >>egy<< >>elo<< >>fie<< >>fkk<< >>fli<< >>gab<< >>gde<< >>gdf<< >>gdk<< >>gdl<< >>gdq<< >>gdu<< >>gea<< >>gek<< >>gew<< >>gex<< >>gez<< >>gft<< >>gha<< >>gho<< >>gid<< >>gis<< >>giz<< >>gji<< >>glo<< >>glw<< >>gnc<< >>gnd<< >>gou<< >>gow<< >>gqa<< >>grd<< >>grr<< >>gru<< >>gwd<< >>gwn<< >>har<< >>hau<< >>hau_Latn<< >>hbb<< >>hbo<< >>hbo_Hebr<< >>hdy<< >>heb<< >>hed<< >>hia<< >>hig<< >>hna<< >>hod<< >>hoh<< >>hrt<< >>hss<< >>huy<< >>hwo<< >>hya<< >>inm<< >>ior<< >>irk<< >>jaf<< >>jbe<< >>jbn<< >>jeu<< >>jia<< >>jie<< >>jii<< >>jim<< >>jmb<< >>jmi<< >>jnj<< >>jpa<< >>jpa_Hebr<< >>jrb<< >>juu<< >>kab<< >>kai<< >>kbz<< >>kcn<< >>kcs<< >>ker<< >>kil<< >>kkr<< >>kks<< >>kna<< >>kof<< >>kot<< >>kpa<< >>kqd<< >>kqp<< >>kqx<< >>ksq<< >>ktb<< >>ktc<< >>kuh<< >>kul<< >>kvf<< >>kvi<< >>kvj<< >>kwl<< >>kxc<< >>ldd<< >>lhs<< >>liq<< >>lln<< >>lme<< >>lsd<< >>maf<< >>mcn<< >>mcw<< >>mdx<< >>meq<< >>mes<< >>mew<< >>mey<< >>mfh<< >>mfi<< >>mfj<< >>mfk<< >>mfl<< >>mfm<< >>mid<< >>mif<< >>mje<< >>mjs<< >>mkf<< >>mlj<< >>mlr<< >>mlt<< >>mlw<< >>mmf<< >>mmy<< >>mou<< >>moz<< >>mpg<< >>mpi<< >>mpk<< >>mqb<< >>mrt<< >>mse<< >>msv<< >>mtl<< >>mub<< >>mug<< >>muj<< >>muu<< >>muy<< >>mvh<< >>mvz<< >>mxf<< >>mxu<< >>mys<< >>myz<< >>mzb<< >>nbh<< >>ndm<< >>ngi<< >>ngs<< >>ngw<< >>ngx<< >>nja<< >>nmi<< >>nnc<< >>nnn<< >>noz<< >>nxm<< >>oar<< >>oar_Hebr<< >>oar_Syrc<< >>orm<< >>oua<< >>pbi<< >>pcw<< >>phn<< >>phn_Phnx<< >>pip<< >>piy<< >>plj<< >>pqa<< >>rel<< >>rif<< >>rif_Latn<< >>rzh<< >>saa<< >>sam<< >>say<< >>scw<< >>sds<< >>sgw<< >>she<< >>shi<< >>shi_Latn<< >>shv<< >>shy<< >>shy_Latn<< >>sid<< >>sir<< >>siz<< >>sjs<< >>smp<< >>sok<< >>som<< >>sor<< >>sqr<< >>sqt<< >>ssn<< >>ssy<< >>stv<< >>sur<< >>swn<< >>swq<< >>swy<< >>syc<< >>syk<< >>syn<< >>syr<< >>tak<< >>tal<< >>tan<< >>taq<< >>tax<< >>tdk<< >>tez<< >>tgd<< >>thv<< >>tia<< >>tig<< >>tir<< >>tjo<< >>tmc<< >>tmh<< >>tmr<< >>tmr_Hebr<< >>tng<< >>tqq<< >>trg<< >>trj<< >>tru<< >>tsb<< >>tsh<< >>ttr<< >>twc<< >>tzm<< >>tzm_Latn<< >>tzm_Tfng<< >>ubi<< >>udl<< >>uga<< >>vem<< >>wal<< >>wbj<< >>wji<< >>wka<< >>wle<< >>xaa<< >>xan<< >>xeb<< >>xed<< >>xhd<< >>xmd<< >>xmj<< >>xna<< >>xpu<< >>xqt<< >>xsa<< >>ymm<< >>zah<< >>zay<< >>zaz<< >>zen<< >>zgh<< >>zim<< >>ziz<< >>zns<< >>zrn<< >>zua<< >>zuy<< >>zwa<<
+- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-afa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip)
+- **Resources for more information:**
+  -  [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-afa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-29)
+  - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+  - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
+  - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
+  - [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
+  - [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
+
+This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>aar<<`
+
+## Uses
+
+This model can be used for translation and text-to-text generation.
+
+## Risks, Limitations and Biases
+
+**CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+## How to Get Started With the Model
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>kab<< Tu seras parmi nous demain.",
+    ">>heb<< Let's get out of here while we can."
+]
+
+model_name = "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-afa"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
+
+for t in translated:
+    print( tokenizer.decode(t, skip_special_tokens=True) )
+
+# expected output:
+#     Azekka ad tiliḍ yid-i
+#     בוא נצא מכאן כל עוד אנחנו יכולים.
+```
+
+You can also use OPUS-MT models with the transformers pipelines, for example:
+
+```python
+from transformers import pipeline
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-afa")
+print(pipe(">>kab<< Tu seras parmi nous demain."))
+
+# expected output: Azekka ad tiliḍ yid-i
+```
+
+## Training
+
+- **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+- **Pre-processing**: SentencePiece (spm32k,spm32k)
+- **Model Type:**  transformer-big
+- **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-afa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip)
+- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+## Evaluation
+
+* [Model scores at the OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-afa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-29)
+* test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-afa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
+* test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-afa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt)
+* benchmark results: [benchmark_results.txt](benchmark_results.txt)
+* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
+
+| langpair | testset | chr-F | BLEU  | #sent | #words |
+|----------|---------|-------|-------|-------|--------|
+| deu-ara | tatoeba-test-v2021-08-07 | 0.49517 | 20.2 | 1209 | 6324 |
+| deu-heb | tatoeba-test-v2021-08-07 | 0.56943 | 35.8 | 3090 | 20341 |
+| eng-ara | tatoeba-test-v2021-08-07 | 0.46273 | 17.3 | 10305 | 61356 |
+| eng-heb | tatoeba-test-v2021-08-07 | 0.57708 | 34.9 | 10519 | 63628 |
+| eng-mlt | tatoeba-test-v2021-08-07 | 0.61044 | 29.5 | 203 | 899 |
+| fra-ara | tatoeba-test-v2021-08-07 | 0.42223 | 10.4 | 1569 | 7956 |
+| fra-heb | tatoeba-test-v2021-08-07 | 0.58681 | 37.5 | 3281 | 20655 |
+| por-heb | tatoeba-test-v2021-08-07 | 0.61593 | 41.0 | 719 | 4423 |
+| spa-ara | tatoeba-test-v2021-08-07 | 0.53669 | 23.9 | 1511 | 7547 |
+| spa-heb | tatoeba-test-v2021-08-07 | 0.61966 | 41.2 | 1849 | 12112 |
+| deu-ara | flores101-devtest | 0.47927 | 15.7 | 1012 | 21357 |
+| eng-hau | flores101-devtest | 0.47807 | 19.0 | 1012 | 27730 |
+| eng-mlt | flores101-devtest | 0.67196 | 32.9 | 1012 | 22169 |
+| fra-mlt | flores101-devtest | 0.56271 | 19.9 | 1012 | 22169 |
+| por-heb | flores101-devtest | 0.49378 | 19.6 | 1012 | 20749 |
+| spa-ara | flores101-devtest | 0.44988 | 11.7 | 1012 | 21357 |
+| deu-ara | flores200-devtest | 0.661 | 0.0 | 1012 | 5 |
+| deu-hau | flores200-devtest | 0.40471 | 11.4 | 1012 | 27730 |
+| deu-heb | flores200-devtest | 0.48645 | 18.1 | 1012 | 20238 |
+| deu-mlt | flores200-devtest | 0.54079 | 17.5 | 1012 | 22169 |
+| eng-ara | flores200-devtest | 0.627 | 0.0 | 1012 | 5 |
+| eng-arz | flores200-devtest | 0.42804 | 11.1 | 1012 | 21034 |
+| eng-hau | flores200-devtest | 0.49023 | 20.4 | 1012 | 27730 |
+| eng-heb | flores200-devtest | 0.56635 | 27.1 | 1012 | 20238 |
+| eng-mlt | flores200-devtest | 0.68334 | 34.9 | 1012 | 22169 |
+| eng-som | flores200-devtest | 0.42814 | 9.9 | 1012 | 25991 |
+| fra-ara | flores200-devtest | 0.631 | 0.0 | 1012 | 5 |
+| fra-hau | flores200-devtest | 0.42731 | 13.2 | 1012 | 27730 |
+| fra-heb | flores200-devtest | 0.49683 | 19.1 | 1012 | 20238 |
+| fra-mlt | flores200-devtest | 0.56844 | 20.4 | 1012 | 22169 |
+| por-ara | flores200-devtest | 0.622 | 0.0 | 1012 | 5 |
+| por-hau | flores200-devtest | 0.42593 | 13.6 | 1012 | 27730 |
+| por-heb | flores200-devtest | 0.50345 | 19.7 | 1012 | 20238 |
+| por-mlt | flores200-devtest | 0.58913 | 21.5 | 1012 | 22169 |
+| spa-ara | flores200-devtest | 0.587 | 0.0 | 1012 | 5 |
+| spa-hau | flores200-devtest | 0.40309 | 9.4 | 1012 | 27730 |
+| spa-heb | flores200-devtest | 0.45249 | 13.5 | 1012 | 20238 |
+| spa-mlt | flores200-devtest | 0.51077 | 12.7 | 1012 | 22169 |
+| eng-hau | newstest2021 | 0.43617 | 13.1 | 1000 | 32966 |
+| deu-hau | ntrex128 | 0.41931 | 12.5 | 1997 | 54982 |
+| deu-heb | ntrex128 | 0.43961 | 13.3 | 1997 | 39624 |
+| deu-mlt | ntrex128 | 0.49871 | 15.1 | 1997 | 43308 |
+| eng-hau | ntrex128 | 0.51601 | 23.2 | 1997 | 54982 |
+| eng-heb | ntrex128 | 0.50625 | 20.3 | 1997 | 39624 |
+| eng-mlt | ntrex128 | 0.62552 | 29.0 | 1997 | 43308 |
+| eng-som | ntrex128 | 0.46845 | 13.5 | 1997 | 49351 |
+| fra-hau | ntrex128 | 0.43729 | 14.5 | 1997 | 54982 |
+| fra-heb | ntrex128 | 0.43855 | 13.9 | 1997 | 39624 |
+| fra-mlt | ntrex128 | 0.51640 | 17.3 | 1997 | 43308 |
+| fra-som | ntrex128 | 0.41813 | 9.6 | 1997 | 49351 |
+| por-hau | ntrex128 | 0.44408 | 15.1 | 1997 | 54982 |
+| por-heb | ntrex128 | 0.45739 | 15.0 | 1997 | 39624 |
+| por-mlt | ntrex128 | 0.53719 | 18.2 | 1997 | 43308 |
+| por-som | ntrex128 | 0.41367 | 9.3 | 1997 | 49351 |
+| spa-hau | ntrex128 | 0.44695 | 14.8 | 1997 | 54982 |
+| spa-heb | ntrex128 | 0.45509 | 14.5 | 1997 | 39624 |
+| spa-mlt | ntrex128 | 0.53631 | 17.7 | 1997 | 43308 |
+| spa-som | ntrex128 | 0.41755 | 9.1 | 1997 | 49351 |
+| eng-ara | tico19-test | 0.56288 | 25.4 | 2100 | 51339 |
+| eng-hau | tico19-test | 0.50060 | 22.2 | 2100 | 64509 |
+| fra-amh | tico19-test | 3.575 | 1.3 | 2100 | 44782 |
+| fra-hau | tico19-test | 5.071 | 1.8 | 2100 | 64509 |
+| fra-orm | tico19-test | 4.044 | 1.8 | 2100 | 50032 |
+| fra-som | tico19-test | 2.698 | 0.9 | 2100 | 63654 |
+| fra-tir | tico19-test | 4.151 | 1.4 | 2100 | 46685 |
+| por-amh | tico19-test | 3.799 | 1.4 | 2100 | 44782 |
+| por-ara | tico19-test | 0.44442 | 16.0 | 2100 | 51339 |
+| por-hau | tico19-test | 5.786 | 2.0 | 2100 | 64509 |
+| por-orm | tico19-test | 4.613 | 2.0 | 2100 | 50032 |
+| por-som | tico19-test | 3.413 | 1.2 | 2100 | 63654 |
+| por-tir | tico19-test | 5.092 | 1.6 | 2100 | 46685 |
+| spa-amh | tico19-test | 3.831 | 1.4 | 2100 | 44782 |
+| spa-ara | tico19-test | 0.45429 | 16.5 | 2100 | 51339 |
+| spa-hau | tico19-test | 5.790 | 1.9 | 2100 | 64509 |
+| spa-orm | tico19-test | 4.617 | 1.9 | 2100 | 50032 |
+| spa-som | tico19-test | 3.402 | 1.2 | 2100 | 63654 |
+| spa-tir | tico19-test | 5.033 | 1.6 | 2100 | 46685 |
+
+## Citation Information
+
+* Publications: [Democratizing neural machine translation with OPUS-MT](https://doi.org/10.1007/s10579-023-09704-w) and [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
+
+```bibtex
+@article{tiedemann2023democratizing,
+  title={Democratizing neural machine translation with {OPUS-MT}},
+  author={Tiedemann, J{\"o}rg and Aulamo, Mikko and Bakshandaeva, Daria and Boggia, Michele and Gr{\"o}nroos, Stig-Arne and Nieminen, Tommi and Raganato, Alessandro and Scherrer, Yves and Vazquez, Raul and Virpioja, Sami},
+  journal={Language Resources and Evaluation},
+  number={58},
+  pages={713--755},
+  year={2023},
+  publisher={Springer Nature},
+  issn={1574-0218},
+  doi={10.1007/s10579-023-09704-w}
+}
+
+@inproceedings{tiedemann-thottingal-2020-opus,
+    title = "{OPUS}-{MT} {--} Building open translation services for the World",
+    author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},
+    booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Lisboa, Portugal",
+    publisher = "European Association for Machine Translation",
+    url = "https://aclanthology.org/2020.eamt-1.61",
+    pages = "479--480",
+}
+
+@inproceedings{tiedemann-2020-tatoeba,
+    title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
+    author = {Tiedemann, J{\"o}rg},
+    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.wmt-1.139",
+    pages = "1174--1182",
+}
+```
+
+## Acknowledgements
+
+The work is supported by the [HPLT project](https://hplt-project.org/), funded by the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland, and the [EuroHPC supercomputer LUMI](https://www.lumi-supercomputer.eu/).
+
+## Model conversion info
+
+* transformers version: 4.45.1
+* OPUS-MT git hash: 0882077
+* port time: Tue Oct  8 00:25:35 EEST 2024
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,158 @@
+multi-multi	tatoeba-test-v2020-07-28-v2023-09-26	0.38446	15.7	10000	60769
+deu-amh	flores101-devtest	0.24177	3.2	1012	17752
+deu-ara	flores101-devtest	0.47927	15.7	1012	21357
+deu-hau	flores101-devtest	0.39583	10.6	1012	27730
+deu-orm	flores101-devtest	0.27616	1.6	1012	22305
+deu-som	flores101-devtest	0.36012	5.6	1012	25991
+eng-amh	flores101-devtest	0.30626	5.7	1012	17752
+eng-hau	flores101-devtest	0.47807	19.0	1012	27730
+eng-mlt	flores101-devtest	0.67196	32.9	1012	22169
+eng-orm	flores101-devtest	0.27540	1.9	1012	22305
+fra-amh	flores101-devtest	0.23655	2.7	1012	17752
+fra-mlt	flores101-devtest	0.56271	19.9	1012	22169
+por-heb	flores101-devtest	0.49378	19.6	1012	20749
+spa-ara	flores101-devtest	0.44988	11.7	1012	21357
+deu-acm	flores200-devtest	0.15386	1.8	1012	20497
+deu-amh	flores200-devtest	0.25718	3.7	1012	17752
+deu-apc	flores200-devtest	0.28133	3.1	1012	19476
+deu-ara	flores200-devtest	0.661	0.0	1012	5
+deu-arz	flores200-devtest	0.36318	7.3	1012	21034
+deu-hau	flores200-devtest	0.40471	11.4	1012	27730
+deu-heb	flores200-devtest	0.48645	18.1	1012	20238
+deu-kab	flores200-devtest	0.26058	4.0	1012	24833
+deu-mlt	flores200-devtest	0.54079	17.5	1012	22169
+deu-som	flores200-devtest	0.36953	6.0	1012	25991
+deu-tir	flores200-devtest	0.12053	0.5	1012	19825
+eng-acm	flores200-devtest	0.25847	5.7	1012	20497
+eng-amh	flores200-devtest	0.32177	6.1	1012	17752
+eng-apc	flores200-devtest	0.29364	4.6	1012	19476
+eng-ara	flores200-devtest	0.627	0.0	1012	5
+eng-arz	flores200-devtest	0.42804	11.1	1012	21034
+eng-hau	flores200-devtest	0.49023	20.4	1012	27730
+eng-heb	flores200-devtest	0.56635	27.1	1012	20238
+eng-kab	flores200-devtest	0.24787	4.6	1012	24833
+eng-mlt	flores200-devtest	0.68334	34.9	1012	22169
+eng-som	flores200-devtest	0.42814	9.9	1012	25991
+eng-tir	flores200-devtest	0.15638	1.0	1012	19825
+fra-acm	flores200-devtest	0.18465	2.8	1012	20497
+fra-amh	flores200-devtest	0.25459	3.2	1012	17752
+fra-apc	flores200-devtest	0.26330	2.3	1012	19476
+fra-ara	flores200-devtest	0.631	0.0	1012	5
+fra-arz	flores200-devtest	0.37400	7.7	1012	21034
+fra-hau	flores200-devtest	0.42731	13.2	1012	27730
+fra-heb	flores200-devtest	0.49683	19.1	1012	20238
+fra-kab	flores200-devtest	0.25304	3.9	1012	24833
+fra-mlt	flores200-devtest	0.56844	20.4	1012	22169
+fra-som	flores200-devtest	0.39543	7.3	1012	25991
+fra-tir	flores200-devtest	0.12494	0.4	1012	19825
+por-acm	flores200-devtest	0.16154	2.0	1012	20497
+por-amh	flores200-devtest	0.25501	3.4	1012	17752
+por-apc	flores200-devtest	0.29378	3.2	1012	19476
+por-ara	flores200-devtest	0.622	0.0	1012	5
+por-arz	flores200-devtest	0.36797	7.0	1012	21034
+por-hau	flores200-devtest	0.42593	13.6	1012	27730
+por-heb	flores200-devtest	0.50345	19.7	1012	20238
+por-kab	flores200-devtest	0.27366	4.7	1012	24833
+por-mlt	flores200-devtest	0.58913	21.5	1012	22169
+por-som	flores200-devtest	0.38536	7.1	1012	25991
+por-tir	flores200-devtest	0.11874	0.5	1012	19825
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+spa-tir	tico19-test	5.033	1.6	2100	46685

config.json

@@ -0,0 +1,41 @@
+{
+  "_name_or_path": "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-afa",
+  "activation_dropout": 0.0,
+  "activation_function": "relu",
+  "architectures": [
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+  "decoder_vocab_size": 61815,
+  "dropout": 0.1,
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+  "init_std": 0.02,
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+  "max_position_embeddings": 1024,
+  "model_type": "marian",
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+  "num_hidden_layers": 6,
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+  "scale_embedding": true,
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+  "static_position_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.1",
+  "use_cache": true,
+  "vocab_size": 61815
+}

generation_config.json

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+{
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+  "bad_words_ids": [
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+  "max_length": 512,
+  "num_beams": 4,
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+  "transformers_version": "4.45.1"
+}

model.safetensors

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pytorch_model.bin

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special_tokens_map.json

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target.spm

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tokenizer_config.json

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