metadata

pipeline_tag: translation
language:
  - multilingual
  - af
  - am
  - ar
  - as
  - az
  - be
  - bg
  - bn
  - br
  - bs
  - ca
  - cs
  - cy
  - da
  - de
  - el
  - en
  - eo
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - fy
  - ga
  - gd
  - gl
  - gu
  - ha
  - he
  - hi
  - hr
  - hu
  - hy
  - id
  - is
  - it
  - ja
  - jv
  - ka
  - kk
  - km
  - kn
  - ko
  - ku
  - ky
  - la
  - lo
  - lt
  - lv
  - mg
  - mk
  - ml
  - mn
  - mr
  - ms
  - my
  - ne
  - nl
  - 'no'
  - om
  - or
  - pa
  - pl
  - ps
  - pt
  - ro
  - ru
  - sa
  - sd
  - si
  - sk
  - sl
  - so
  - sq
  - sr
  - su
  - sv
  - sw
  - ta
  - te
  - th
  - tl
  - tr
  - ug
  - uk
  - ur
  - uz
  - vi
  - xh
  - yi
  - zh
license: apache-2.0
base_model:
  - FacebookAI/xlm-roberta-large

COMET-partial

This model is based on COMET-early-exit, which is a fork but not compatible with original Unbabel's COMET. To run the model, you need to first install this version of COMET either with:

pip install "git+https://github.com/zouharvi/COMET-early-exit#egg=comet-early-exit&subdirectory=comet_early_exit"

or in editable mode:

git clone https://github.com/zouharvi/COMET-early-exit.git
cd COMET-early-exit
pip3 install -e comet_early_exit

This model is described in the appendix in the paper. It is able to score even incomplete translations (i.e. prefixes of translations):

model = comet_early_exit.load_from_checkpoint(comet_early_exit.download_model("zouharvi/COMET-partial"))
data = [
    {
        "src": "Can I receive my food in 10 to 15 minutes?",
        "mt": "Mohl bych",
    },
    {
        "src": "Can I receive my food in 10 to 15 minutes?",
        "mt": "Mohl bych dostat jídlo",
    },
    {
        "src": "Can I receive my food in 10 to 15 minutes?",
        "mt": "Mohl bych dostat jídlo během 10 či 15 minut?",
    }
]
model_output = model.predict(data, batch_size=8, gpus=1)
print("scores", model_output["scores"])

Outputs (formatted):

scores 89.18  86.52  89.20

This model is based on the work Early-Exit and Instant Confidence Translation Quality Estimation which can be cited as:

@misc{zouhar2025earlyexitinstantconfidencetranslation,
      title={Early-Exit and Instant Confidence Translation Quality Estimation}, 
      author={Vilém Zouhar and Maike Züfle and Beni Egressy and Julius Cheng and Jan Niehues},
      year={2025},
      eprint={2502.14429},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2502.14429}, 
}