How to use SamiKazrboubi/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SamiKazrboubi/result_model") sentences = [ "A man, woman, and child enjoying themselves on a beach.", "A family of three is at the mall shopping.", "An actress and her favorite assistant talk a walk in the city.", "The woman is nake." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
