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--- |
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language: |
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- multilingual |
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- ha |
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- is |
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- ja |
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- cs |
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- ru |
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- zh |
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- de |
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- en |
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license: mit |
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tags: |
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- translation |
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- wmt21 |
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--- |
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# WMT 21 En-X |
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WMT 21 En-X is a 4.7B multilingual encoder-decoder (seq-to-seq) model trained for one-to-many multilingual translation. |
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It was introduced in this [paper](https://arxiv.org/abs/2108.03265) and first released in [this](https://github.com/pytorch/fairseq/tree/main/examples/wmt21) repository. |
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The model can directly translate English text into 7 other languages: Hausa (ha), Icelandic (is), Japanese (ja), Czech (cs), Russian (ru), Chinese (zh), German (de). |
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To translate into a target language, the target language id is forced as the first generated token. |
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To force the target language id as the first generated token, pass the `forced_bos_token_id` parameter to the `generate` method. |
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*Note: `M2M100Tokenizer` depends on `sentencepiece`, so make sure to install it before running the example.* |
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To install `sentencepiece` run `pip install sentencepiece` |
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Since the model was trained with domain tags, you should prepend them to the input as well. |
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* "wmtdata newsdomain": Use for sentences in the news domain |
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* "wmtdata otherdomain": Use for sentences in all other domain |
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```python |
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer |
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model = AutoModelForSeq2SeqLM.from_pretrained("facebook/wmt21-dense-24-wide-en-x") |
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tokenizer = AutoTokenizer.from_pretrained("facebook/wmt21-dense-24-wide-en-x") |
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inputs = tokenizer("wmtdata newsdomain One model for many languages.", return_tensors="pt") |
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# translate English to German |
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generated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.get_lang_id("de")) |
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tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) |
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# => "Ein Modell für viele Sprachen." |
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# translate English to Icelandic |
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generated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.get_lang_id("is")) |
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tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) |
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# => "Ein fyrirmynd fyrir mörg tungumál." |
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``` |
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See the [model hub](https://huggingface.co/models?filter=wmt21) to look for more fine-tuned versions. |
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## Languages covered |
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English (en), Hausa (ha), Icelandic (is), Japanese (ja), Czech (cs), Russian (ru), Chinese (zh), German (de) |
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## BibTeX entry and citation info |
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``` |
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@inproceedings{tran2021facebook |
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title={Facebook AI’s WMT21 News Translation Task Submission}, |
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author={Chau Tran and Shruti Bhosale and James Cross and Philipp Koehn and Sergey Edunov and Angela Fan}, |
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booktitle={Proc. of WMT}, |
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year={2021}, |
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} |
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``` |
