How to use whybe-choi/Qwen3-VL-Embedding-2B-ko-vdr-preview-v0.2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("whybe-choi/Qwen3-VL-Embedding-2B-ko-vdr-preview-v0.2") sentences = [ "What are the envisaged outputs of the digital health strategy mentioned in the text?", "data/images/en/colpali/dd11bda4992c17a2949b9af53e136c03.jpg", "data/images/en/colpali/98e4e11f3f014db6f8d59038deb43f9e.jpg", "data/images/en/colpali/5e4bda61ceeadc967df5475b4c03ec70.jpg", "data/images/en/colpali/b5eb523647af1c190b70986dad5f702f.jpg", "data/images/en/colpali/03476f161be526647086f92ee62676e5.jpg", "data/images/en/colpali/16f4cc89764a1b9700b9337a8d5c247d.jpg", "data/images/en/colpali/a5537a0ece08b55f500ab206fc7020da.jpg", "data/images/en/colpali/cf7a303df1a78d4ce5f21a65fa79d452.jpg" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [9, 9]
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