How to use kiel2/Kiel-Embed-2-Vision with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kiel2/Kiel-Embed-2-Vision") sentences = [ "On Oct. 10 , an 18-year-old freshman member of the men 's swim team jumped from the same 10th-floor ledge .", "\" It 's a blond-haired woman wearing a Cartier watch on her wrist , \" the source said .", "He was sentenced to more than seven years in prison after pleading guilty to charges including securities fraud .", "On Oct. 10 , an 18-year-old freshman from Dayton , Ohio , climbed over the same 10th-floor ledge and plunged to his death ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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