language: multilingual
license: mit
tags:
- translation
- wmt21
WMT 21 En-X
WMT 21 En-X is a 4.7B multilingual encoder-decoder (seq-to-seq) model trained for one-to-many multilingual translation. It was introduced in this paper and first released in this repository.
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).
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.
Note: M2M100Tokenizer
depends on sentencepiece
, so make sure to install it before running the example.
To install sentencepiece
run pip install sentencepiece
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("facebook/wmt21-dense-24-wide-en-x")
tokenizer = AutoTokenizer.from_pretrained("facebook/wmt21-dense-24-wide-en-x")
inputs = tokenizer("One model for many languages.", return_tensors="pt")
# translate English to German
generated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.get_lang_id("de"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
# => "Ein Modell für viele Sprachen."
# translate English to Icelandic
generated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.get_lang_id("is"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
# => "Ein fyrirmynd fyrir mörg tungumál."
See the model hub to look for more fine-tuned versions.
Languages covered
English (en), Hausa (ha), Icelandic (is), Japanese (ja), Czech (cs), Russian (ru), Chinese (zh), German (de)
BibTeX entry and citation info
@inproceedings{tran2021facebook
title={Facebook AI’s WMT21 News Translation Task Submission},
author={Chau Tran and Shruti Bhosale and James Cross and Philipp Koehn and Sergey Edunov and Angela Fan},
booktitle={Proc. of WMT},
year={2021},
}