metadata
language:
- ko
pipeline_tag: sentence-similarity tags: - sentence-transformers - sentence-similarity - transformers
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)