How to use 1HeroX1/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("1HeroX1/result_model") sentences = [ "A woman wearing all white and eating, walks next to a man holding a briefcase.", "A married couple is walking next to each other.", "The women do not care what clothes they wear.", "The diners are at a restaurant." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
