Edit model card

ํ•œ๊ตญ์–ด์™€ ์˜์–ด์˜ nli, sts๋ฐ์ดํ„ฐ๋ฅผ klue/roberta-base์— ํ•™์Šต์‹œํ‚จ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.

from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity
query = ['๊ทธ๋Š” ๊ทธ๋…€๋ฅผ ์ข‹์•„ํ•œ๋‹ค.']
sentences = ["he love her", "he hate her", '๊ทธ๋…€๋Š” ๊ทธ๋ฅผ ์‹ซ์–ดํ•œ๋‹ค.','attention is all you need']

emb1 = model.encode(query)
emb2 = model.encode(sentences)
print(cosine_similarity(emb1,emb2))
-> array([[0.62751913, 0.23996451, 0.30788696, 0.08123618]], dtype=float32)
Downloads last month
7
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.