---
title: mbart-large-50-one-to-many-mmt
canonical_url: "https://www.modelscope.cn/models/facebook/mbart-large-50-one-to-many-mmt"
md_url: "https://www.modelscope.cn/models/facebook/mbart-large-50-one-to-many-mmt.md"
repository: facebook/mbart-large-50-one-to-many-mmt
last_updated: 2025-05-20
pipeline_tag: text2text-generation
tasks:
  - text2text-generation
model_type:
  - mbart
architectures:
  - MBartForConditionalGeneration
library_name:
  - transformer
  - tensorflow
  - pytorch
frameworks:
  - pytorch
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
downloads: 336
stars: 0
tags:
  - mbart-50
---

# mbart-large-50-one-to-many-mmt

> mbart-large-50-one-to-many-mmt - facebook 在 ModelScope 开源的模型。mBART-50 one to many multilingual machine translation

- **Repository**: facebook/mbart-large-50-one-to-many-mmt
- **Tasks**: text2text-generation
- **Tags**: mbart-50
- **Downloads**: 336
- **Stars**: 0
- **Last updated**: 2025-05-20

Source: https://www.modelscope.cn/models/facebook/mbart-large-50-one-to-many-mmt

---

# mBART-50 one to many multilingual machine translation


This model is a fine-tuned checkpoint of [mBART-large-50](https://huggingface.co/facebook/mbart-large-50). `mbart-large-50-one-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 English to other 49 languages mentioned below. 
To translate into a target language, the target language id is forced as the first generated token. To force the
target language id as the first generated token, pass the `forced_bos_token_id` parameter to the `generate` method.

```python
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
article_en = "The head of the United Nations says there is no military solution in Syria"
model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt")
tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", src_lang="en_XX")

model_inputs = tokenizer(article_en, return_tensors="pt")

# translate from English to Hindi
generated_tokens = model.generate(
    **model_inputs,
    forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
)
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
# => 'संयुक्त राष्ट्र के नेता कहते हैं कि सीरिया में कोई सैन्य समाधान नहीं है'

# translate from English to Chinese
generated_tokens = model.generate(
    **model_inputs,
    forced_bos_token_id=tokenizer.lang_code_to_id["zh_CN"]
)
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
# => '联合国首脑说,叙利亚没有军事解决办法'
```

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}
}
```