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leewaay/kpf-bert-base-klueSTS-cross
kpf-bert-base-klueSTS-cross is a sentence similarity model from leewaay. Use it when you need a score for how close two texts are. It is set up for sentence-transformers.
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 sent…
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From the Hugging Face model README
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.
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)