How to use thelocalhost/fpml-semantic-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thelocalhost/fpml-semantic-model") sentences = [ "Find the element that handles identifies the underlying asset when it is an exchange-traded fund.", "[exchangeTradedFund]: Identifies the underlying asset when it is an exchange-traded fund.", "[mutualFund]: Identifies the class of unit issued by a fund.", "[lcIssuanceFeePayment]: No description available" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
