How to use aelmah/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aelmah/result_model") sentences = [ "A woman is walking across the street eating a banana, while a man is following with his briefcase.", "two coworkers cross pathes on a street", "The kids are frowning", "A person is outdoors, on a horse." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
