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@@ -114,6 +114,7 @@ This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus
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  - More information about released models for this language pair: [OPUS-MT afa-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afa-eng/README.md)
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  - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
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  - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
 
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  - [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
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  ## Uses
@@ -171,6 +172,7 @@ print(pipe("لا أريد أن أبدو غبيّا."))
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  ## Evaluation
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  * test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.test.txt)
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  * test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.eval.txt)
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  * benchmark results: [benchmark_results.txt](benchmark_results.txt)
@@ -184,7 +186,7 @@ print(pipe("لا أريد أن أبدو غبيّا."))
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  * 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.)
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- ```
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  @article{tiedemann2023democratizing,
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  title={Democratizing neural machine translation with {OPUS-MT}},
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  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},
@@ -224,11 +226,11 @@ print(pipe("لا أريد أن أبدو غبيّا."))
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  ## Acknowledgements
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- 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/).
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  ## Model conversion info
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  * transformers version: 4.45.1
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  * OPUS-MT git hash: a44ab31
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- * port time: Sun Oct 6 18:15:21 EEST 2024
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  * port machine: LM0-400-22516.local
 
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  - More information about released models for this language pair: [OPUS-MT afa-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afa-eng/README.md)
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  - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
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  - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
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+ - [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
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  - [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
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  ## Uses
 
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  ## Evaluation
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+ * [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/afa-eng/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-08-17)
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  * test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.test.txt)
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  * test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opusTCv20230926max50+bt+jhubc_transformer-big_2024-08-17.eval.txt)
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  * benchmark results: [benchmark_results.txt](benchmark_results.txt)
 
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  * 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.)
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+ ```bibtex
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  @article{tiedemann2023democratizing,
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  title={Democratizing neural machine translation with {OPUS-MT}},
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  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},
 
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  ## Acknowledgements
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+ 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/).
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  ## Model conversion info
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  * transformers version: 4.45.1
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  * OPUS-MT git hash: a44ab31
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+ * port time: Sun Oct 6 21:06:57 EEST 2024
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  * port machine: LM0-400-22516.local