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README.md

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+---
+language:
+- ca
+- cat+oci+spa
+- en
+- es
+
+tags:
+- translation
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-en-cat_oci_spa
+  results:
+  - task:
+      name: Translation eng-cat
+      type: translation
+      args: eng-cat
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng cat devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 41.5
+  - task:
+      name: Translation eng-oci
+      type: translation
+      args: eng-oci
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng oci devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.4
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.1
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: news-test2008
+      type: news-test2008
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 30.0
+  - task:
+      name: Translation eng-cat
+      type: translation
+      args: eng-cat
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-cat
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 47.8
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 57.0
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 52.5
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: newstest2009
+      type: wmt-2009-news
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 30.5
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: newstest2010
+      type: wmt-2010-news
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 37.4
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: newstest2011
+      type: wmt-2011-news
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 39.1
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: newstest2012
+      type: wmt-2012-news
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 39.6
+  - task:
+      name: Translation eng-spa
+      type: translation
+      args: eng-spa
+    dataset:
+      name: newstest2013
+      type: wmt-2013-news
+      args: eng-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 35.8
+---
+# opus-mt-tc-big-en-cat_oci_spa
+
+Neural machine translation model for translating from English (en) to unknown (cat+oci+spa).
+
+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: 2022-03-13
+* source language(s): eng
+* target language(s): cat spa
+* valid target language labels: >>cat<< >>spa<<
+* model: transformer-big
+* data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+* tokenization: SentencePiece (spm32k,spm32k)
+* original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-cat+oci+spa/opusTCv20210807+bt_transformer-big_2022-03-13.zip)
+* more information released models: [OPUS-MT eng-cat+oci+spa README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-cat+oci+spa/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. `>>cat<<`
+
+## Usage
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>spa<< Why do you want Tom to go there with me?",
+    ">>spa<< She forced him to eat spinach."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-en-cat_oci_spa"
+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:
+#     ¿Por qué quieres que Tom vaya conmigo?
+#     Ella lo obligó a comer espinacas.
+```
+
+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-en-cat_oci_spa")
+print(pipe(">>spa<< Why do you want Tom to go there with me?"))
+
+# expected output: ¿Por qué quieres que Tom vaya conmigo?
+```
+
+## Benchmarks
+
+* test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-cat+oci+spa/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt)
+* test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-cat+oci+spa/opusTCv20210807+bt_transformer-big_2022-03-13.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 |
+|----------|---------|-------|-------|-------|--------|
+| eng-cat | tatoeba-test-v2021-08-07 | 0.66414 | 47.8 | 1631 | 12344 |
+| eng-spa | tatoeba-test-v2021-08-07 | 0.73725 | 57.0 | 16583 | 134710 |
+| eng-cat | flores101-devtest | 0.66071 | 41.5 | 1012 | 27304 |
+| eng-oci | flores101-devtest | 0.56192 | 25.4 | 1012 | 27305 |
+| eng-spa | flores101-devtest | 0.56288 | 28.1 | 1012 | 29199 |
+| eng-spa | newssyscomb2009 | 0.58431 | 31.4 | 502 | 12503 |
+| eng-spa | news-test2008 | 0.56622 | 30.0 | 2051 | 52586 |
+| eng-spa | newstest2009 | 0.57988 | 30.5 | 2525 | 68111 |
+| eng-spa | newstest2010 | 0.62343 | 37.4 | 2489 | 65480 |
+| eng-spa | newstest2011 | 0.62424 | 39.1 | 3003 | 79476 |
+| eng-spa | newstest2012 | 0.63006 | 39.6 | 3003 | 79006 |
+| eng-spa | newstest2013 | 0.60291 | 35.8 | 3000 | 70528 |
+| eng-spa | tico19-test | 0.73224 | 52.5 | 2100 | 66563 |
+
+## 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: 3405783
+* port time: Wed Apr 13 16:40:45 EEST 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,23 @@
+eng-cat	flores101-dev	0.65604	41.5	997	25962
+eng-oci	flores101-dev	0.56013	26.2	997	25819
+eng-spa	flores101-dev	0.55897	27.9	997	27793
+eng-cat	flores101-devtest	0.66071	41.5	1012	27304
+eng-oci	flores101-devtest	0.56192	25.4	1012	27305
+eng-spa	flores101-devtest	0.56288	28.1	1012	29199
+eng-spa	newssyscomb2009	0.58431	31.4	502	12503
+eng-spa	news-test2008	0.56622	30.0	2051	52586
+eng-spa	newstest2009	0.57988	30.5	2525	68111
+eng-spa	newstest2010	0.62343	37.4	2489	65480
+eng-spa	newstest2011	0.62424	39.1	3003	79476
+eng-spa	newstest2012	0.63006	39.6	3003	79006
+eng-spa	newstest2013	0.60291	35.8	3000	70528
+eng-cat	tatoeba-test-v2020-07-28	0.66414	47.8	1631	12344
+eng-oci	tatoeba-test-v2020-07-28	0.29240	7.6	841	5219
+eng-spa	tatoeba-test-v2020-07-28	0.71865	54.7	10000	77311
+eng-cat	tatoeba-test-v2021-03-30	0.66414	47.8	1631	12344
+eng-oci	tatoeba-test-v2021-03-30	0.29229	7.6	842	5225
+eng-spa	tatoeba-test-v2021-03-30	0.72447	55.6	11940	93423
+eng-cat	tatoeba-test-v2021-08-07	0.66414	47.8	1631	12344
+eng-oci	tatoeba-test-v2021-08-07	0.29240	7.6	841	5219
+eng-spa	tatoeba-test-v2021-08-07	0.73725	57.0	16583	134710
+eng-spa	tico19-test	0.73224	52.5	2100	66563

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+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 54660
+}

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