sentence-transformers 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] 
