Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:10501
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use DolphaGo/klue-roberta-base-klue-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DolphaGo/klue-roberta-base-klue-sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DolphaGo/klue-roberta-base-klue-sts") sentences = [ "조명등 낮에 키려고 하지마", "아침 샤워는 꼭 찬물 말고 더운물로 해줘", "일단 숙소는 4인가족이 머무르기 충분한공간입니다", "올드 시티의 그랜드 마스터 궁전, 고고학 박물관 등을 주로 구경한다면 최고의 위치입니다." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle