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+*.spm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- da
+- gmq
+- is
+- nb
+- no
+- ru
+- sv
+- uk
+- zle
+
+tags:
+- translation
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-gmq-zle
+  results:
+  - task:
+      name: Translation dan-rus
+      type: translation
+      args: dan-rus
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan rus devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.6
+  - task:
+      name: Translation dan-ukr
+      type: translation
+      args: dan-ukr
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan ukr devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.5
+  - task:
+      name: Translation nob-rus
+      type: translation
+      args: nob-rus
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob rus devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.1
+  - task:
+      name: Translation nob-ukr
+      type: translation
+      args: nob-ukr
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob ukr devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.6
+  - task:
+      name: Translation swe-rus
+      type: translation
+      args: swe-rus
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe rus devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.8
+  - task:
+      name: Translation swe-ukr
+      type: translation
+      args: swe-ukr
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe ukr devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.7
+  - task:
+      name: Translation dan-rus
+      type: translation
+      args: dan-rus
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 53.9
+  - task:
+      name: Translation nob-rus
+      type: translation
+      args: nob-rus
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 45.8
+  - task:
+      name: Translation swe-rus
+      type: translation
+      args: swe-rus
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 45.9
+---
+# opus-mt-tc-big-gmq-zle
+
+Neural machine translation model for translating from North Germanic languages (gmq) to East Slavic languages (zle).
+
+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).
+
+* Publications: [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.)
+
+```
+@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",
+}
+```
+
+## Model info
+
+* Release: 2022-03-23
+* source language(s): dan isl nob nor swe
+* target language(s): rus ukr
+* valid target language labels: >>rus<< >>ukr<<
+* model: transformer-big
+* data: opusTCv20210807+pbt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+* tokenization: SentencePiece (spm32k,spm32k)
+* original model: [opusTCv20210807+pbt_transformer-big_2022-03-23.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-zle/opusTCv20210807+pbt_transformer-big_2022-03-23.zip)
+* more information released models: [OPUS-MT gmq-zle README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-zle/README.md)
+* more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian)
+
+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. `>>rus<<`
+
+## Usage
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>bel<< Det er allerede torsdag i morgen.",
+    ">>ukr<< Tom lekte katt och råtta med Mary."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-gmq-zle"
+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:
+#     Гэта ўжо чацвер заўтра.
+#     Том грав кішку і щура з Марією.
+```
+
+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-big-gmq-zle")
+print(pipe(">>bel<< Det er allerede torsdag i morgen."))
+
+# expected output: Гэта ўжо чацвер заўтра.
+```
+
+## Benchmarks
+
+* test set translations: [opusTCv20210807+pbt_transformer-big_2022-03-23.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-zle/opusTCv20210807+pbt_transformer-big_2022-03-23.test.txt)
+* test set scores: [opusTCv20210807+pbt_transformer-big_2022-03-23.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-zle/opusTCv20210807+pbt_transformer-big_2022-03-23.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 |
+|----------|---------|-------|-------|-------|--------|
+| dan-rus | tatoeba-test-v2021-08-07 | 0.72627 | 53.9 | 1713 | 10480 |
+| nob-rus | tatoeba-test-v2021-08-07 | 0.66881 | 45.8 | 1277 | 10659 |
+| swe-rus | tatoeba-test-v2021-08-07 | 0.66248 | 45.9 | 1282 | 7659 |
+| dan-rus | flores101-devtest | 0.53271 | 25.6 | 1012 | 23295 |
+| dan-ukr | flores101-devtest | 0.54273 | 25.5 | 1012 | 22810 |
+| nob-rus | flores101-devtest | 0.50426 | 22.1 | 1012 | 23295 |
+| nob-ukr | flores101-devtest | 0.51156 | 21.6 | 1012 | 22810 |
+| swe-rus | flores101-devtest | 0.53226 | 25.8 | 1012 | 23295 |
+| swe-ukr | flores101-devtest | 0.54257 | 25.7 | 1012 | 22810 |
+
+## Acknowledgements
+
+The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: 1bdabf7
+* port time: Thu Mar 24 02:08:53 EET 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,27 @@
+dan-bel	flores101-dev	0.38828	9.2	997	23996
+dan-rus	flores101-dev	0.53475	26.0	997	22657
+dan-ukr	flores101-dev	0.53315	24.6	997	21841
+isl-bel	flores101-dev	0.29287	5.1	997	23996
+isl-rus	flores101-dev	0.38585	13.9	997	22657
+isl-ukr	flores101-dev	0.36700	11.4	997	21841
+nob-bel	flores101-dev	0.37191	8.3	997	23996
+nob-rus	flores101-dev	0.50038	22.1	997	22657
+nob-ukr	flores101-dev	0.50474	20.8	997	21841
+swe-bel	flores101-dev	0.38670	9.3	997	23996
+swe-rus	flores101-dev	0.53279	26.0	997	22657
+swe-ukr	flores101-dev	0.53440	24.7	997	21841
+dan-bel	flores101-devtest	0.39705	9.9	1012	24829
+dan-rus	flores101-devtest	0.53271	25.6	1012	23295
+dan-ukr	flores101-devtest	0.54273	25.5	1012	22810
+isl-bel	flores101-devtest	0.29058	5.4	1012	24829
+isl-rus	flores101-devtest	0.37416	12.6	1012	23295
+isl-ukr	flores101-devtest	0.36508	11.5	1012	22810
+nob-bel	flores101-devtest	0.38315	8.6	1012	24829
+nob-rus	flores101-devtest	0.50426	22.1	1012	23295
+nob-ukr	flores101-devtest	0.51156	21.6	1012	22810
+swe-bel	flores101-devtest	0.39250	9.6	1012	24829
+swe-rus	flores101-devtest	0.53226	25.8	1012	23295
+swe-ukr	flores101-devtest	0.54257	25.7	1012	22810
+dan-rus	tatoeba-test-v2021-08-07	0.72627	53.9	1713	10480
+nob-rus	tatoeba-test-v2021-08-07	0.66881	45.8	1277	10659
+swe-rus	tatoeba-test-v2021-08-07	0.66248	45.9	1282	7659

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+  "model_type": "marian",
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+  "scale_embedding": true,
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+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 61373
+}

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tokenizer_config.json

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