How to use Ouchbara/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ouchbara/result_model") sentences = [ "A man with blond-hair, and a brown shirt drinking out of a public water fountain.", "A blond man wearing a brown shirt is reading a book on a bench in the park", "The friends scowl at each other over a full dinner table.", "Two adults walk across a street." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
