COMET-early-exit
Collection
Models introduced in the paper Early-Exit and Instant Confidence Translation Quality Estimation https://github.com/zouharvi/COMET-early-exit
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4 items
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Updated
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2
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):
import comet_early_exit
model = comet_early_exit.load_from_checkpoint(comet_early_exit.download_model("zouharvi/COMET-partial"))
data = [
{
"src": "I want to receive my food in 10 to 15 minutes.",
"mt": "Ich werde",
},
{
"src": "I want to receive my food in 10 to 15 minutes.",
"mt": "Ich möchte",
},
{
"src": "I want to receive my food in 10 to 15 minutes.",
"mt": "Ich möchte mein Essen in",
},
{
"src": "I want to receive my food in 10 to 15 minutes.",
"mt": "Ich möchte mein Essen in 10 bis 15 Minuten erhalten.",
},
{
"src": "I want to receive my food in 10 to 15 minutes.",
"mt": "Ich möchte mein Essen in 10 bis 15 Minuten bekommen.",
}
]
model_output = model.predict(data, batch_size=8, gpus=1)
print("scores", model_output["scores"])
Outputs (formatted):
scores 89.26 89.45 89.51 89.48 89.66
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},
}
Base model
FacebookAI/xlm-roberta-large