sentence-transformers How to use irene93/RAG_enhance with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("irene93/RAG_enhance")
sentences = [
"What concern did analysts have regarding Microsoft's canceled data center leases, and how might recent growth in Azure address these concerns?",
"Microsoft's Azure cloud division in particular grew by a third over\nthe quarter. The company says about half of that was contributed by AI, news\nthat could ease worries about a slowdown in demand for the new tech. Some\nanalysts had previously pointed to canceled data center leases by Microsoft as\na sign of excess capacity.",
"The 2-year note <US2YT=RR> yield, which typically moves in\nstep with interest rate expectations for the Federal Reserve,\nfell 2.5 basis points to 3.66%, from 3.685% late on Monday. Oil prices slid on fears of a global recession and dampening\ndemand due to Trump's trade war. U.S. crude <CLc1> fell 2.63% to settle at $60.42 per barrel,\n while Brent <LCOc1> settled at $64.25 per barrel, down 2.44% on\nthe day.",
"They tried to bring back tariffs to save our country, but it\nwas gone. It was too late. Nothing could have been done."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
