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leewaay/kpf-bert-base-klueSTS-cross

This is a sentence-transformers model: A cross encoder trained with the pretrained jinmang2/kpfbert model on the KLUE STS dataset for sentence similarity tasks. It's specifically designed for direct evaluation of sentence pairs, making it highly effective for Re-Ranking and Augmented SBERT for data labeling tasks aimed at enhancing SBERT.

Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import CrossEncoder
pairs = [('Query', 'Paragraph1'), ('Query', 'Paragraph2') , ('Query', 'Paragraph3')]

model = CrossEncoder('leewaay/kpf-bert-base-klueSTS-cross')
scores = model.predict(pairs)
print(scores)

Citing & Authors

Wonseok Lee

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