How to use llm-semantic-router/mmbert-embed-finance with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("llm-semantic-router/mmbert-embed-finance") sentences = [ "What might be contained in Item 8 of a financial document?", "What amount was authorized for future share repurchases by the company as of October 31, 2023?\n\nAnswer: $1.0 billion", "What information is contained in Item 8 of a financial document?\n\nAnswer: Item 8 contains the Financial Statements and Supplementary Data.", "What might be contained in Item 8 of a financial document?\n\nAnswer: Financial Statements and Supplementary Data" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
