How to use summerstars/MARK-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("summerstars/MARK-Embedding") sentences = [ "Nterprise Linux Services is expected to be available before then end of this year.", "Beta versions of Nterprise Linux Services are expected to be available on certain HP ProLiant servers in July.", "Spain turning back the clock on siestas", "I don't like many flavored drinks." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
