How to use LamaDiab/MiniLM-v35-SemanticEngine with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LamaDiab/MiniLM-v35-SemanticEngine") sentences = [ "creamy black varnish for black leathers", "shoe accessory", "the first product scented, nourishing, polishing and preserving all types of leather 50 gr.", "steal the scene t-shirt" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
