How to use lauragobrightly/paolo-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lauragobrightly/paolo-embeddings") sentences = [ "What was the decision about the onboarding flow?", "We decided to use a connect-first approach inspired by the Grammarly model", "The API endpoint returns a 384-dimensional embedding vector", "Yesterday we discussed the new color palette for the website" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
