| --- |
| language: |
| - multilingual |
| - ar |
| - cs |
| - de |
| - en |
| - es |
| - et |
| - fi |
| - fr |
| - gu |
| - hi |
| - it |
| - ja |
| - kk |
| - ko |
| - lt |
| - lv |
| - my |
| - ne |
| - nl |
| - ro |
| - ru |
| - si |
| - tr |
| - vi |
| - zh |
| - af |
| - az |
| - bn |
| - fa |
| - he |
| - hr |
| - id |
| - ka |
| - km |
| - mk |
| - ml |
| - mn |
| - mr |
| - pl |
| - ps |
| - pt |
| - sv |
| - sw |
| - ta |
| - te |
| - th |
| - tl |
| - uk |
| - ur |
| - xh |
| - gl |
| - sl |
| tags: |
| - mbart-50 |
| --- |
| |
| # mBART-50 many to one multilingual machine translation |
|
|
|
|
| This model is a fine-tuned checkpoint of [mBART-large-50](https://huggingface.co/facebook/mbart-large-50). `mbart-large-50-many-to-many-mmt` is fine-tuned for multilingual machine translation. It was introduced in [Multilingual Translation with Extensible Multilingual Pretraining and Finetuning](https://arxiv.org/abs/2008.00401) paper. |
| The model can translate directly between any pair of 50 languages. |
|
|
|
|
| ```python |
| from transformers import MBartForConditionalGeneration, MBart50TokenizerFast |
| |
| article_hi = "संयुक्त राष्ट्र के प्रमुख का कहना है कि सीरिया में कोई सैन्य समाधान नहीं है" |
| article_ar = "الأمين العام للأمم المتحدة يقول إنه لا يوجد حل عسكري في سوريا." |
| |
| model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-one-mmt") |
| tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-one-mmt") |
| |
| # translate Hindi to English |
| tokenizer.src_lang = "hi_IN" |
| encoded_hi = tokenizer(article_hi, return_tensors="pt") |
| generated_tokens = model.generate(**encoded_hi) |
| tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) |
| # => "The head of the UN says there is no military solution in Syria." |
| |
| # translate Arabic to English |
| tokenizer.src_lang = "ar_AR" |
| encoded_ar = tokenizer(article_ar, return_tensors="pt") |
| generated_tokens = model.generate(**encoded_ar) |
| tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) |
| # => "The Secretary-General of the United Nations says there is no military solution in Syria." |
| ``` |
|
|
|
|
| See the [model hub](https://huggingface.co/models?filter=mbart-50) to look for more fine-tuned versions. |
|
|
|
|
| ## Languages covered |
| Arabic (ar_AR), Czech (cs_CZ), German (de_DE), English (en_XX), Spanish (es_XX), Estonian (et_EE), Finnish (fi_FI), French (fr_XX), Gujarati (gu_IN), Hindi (hi_IN), Italian (it_IT), Japanese (ja_XX), Kazakh (kk_KZ), Korean (ko_KR), Lithuanian (lt_LT), Latvian (lv_LV), Burmese (my_MM), Nepali (ne_NP), Dutch (nl_XX), Romanian (ro_RO), Russian (ru_RU), Sinhala (si_LK), Turkish (tr_TR), Vietnamese (vi_VN), Chinese (zh_CN), Afrikaans (af_ZA), Azerbaijani (az_AZ), Bengali (bn_IN), Persian (fa_IR), Hebrew (he_IL), Croatian (hr_HR), Indonesian (id_ID), Georgian (ka_GE), Khmer (km_KH), Macedonian (mk_MK), Malayalam (ml_IN), Mongolian (mn_MN), Marathi (mr_IN), Polish (pl_PL), Pashto (ps_AF), Portuguese (pt_XX), Swedish (sv_SE), Swahili (sw_KE), Tamil (ta_IN), Telugu (te_IN), Thai (th_TH), Tagalog (tl_XX), Ukrainian (uk_UA), Urdu (ur_PK), Xhosa (xh_ZA), Galician (gl_ES), Slovene (sl_SI) |
|
|
|
|
| ## BibTeX entry and citation info |
| ``` |
| @article{tang2020multilingual, |
| title={Multilingual Translation with Extensible Multilingual Pretraining and Finetuning}, |
| author={Yuqing Tang and Chau Tran and Xian Li and Peng-Jen Chen and Naman Goyal and Vishrav Chaudhary and Jiatao Gu and Angela Fan}, |
| year={2020}, |
| eprint={2008.00401}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL} |
| } |
| ``` |
