sentence-transformers How to use whybe-choi/Qwen3-VL-Embedding-2B-ko-vdr-preview-v0.3 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("whybe-choi/Qwen3-VL-Embedding-2B-ko-vdr-preview-v0.3")
sentences = [
"공공외교법 제6조 및 제12조에 따른 기본계획 수립과 한국국제교류재단(KF)의 역할, 한러 협력 전략, 다부처 협력 과제들이 어떻게 공공외교의 통합적 추진 체계 강화에 기여했나요?",
"data/images/ko/ko-vdr-public/5364.png",
"data/images/ko/ko-vdr-public/5369.png",
"data/images/ko/ko-vdr-public/6349.png",
"data/images/ko/ko-vdr-public/5357.png",
"data/images/ko/ko-vdr-public/5356.png",
"data/images/ko/ko-vdr-public/904.png",
"data/images/ko/ko-vdr-public/886.png",
"data/images/ko/ko-vdr-public/5379.png"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [9, 9] 
