How to use NickyNicky/bge-base-financial-matryoshka_test_3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NickyNicky/bge-base-financial-matryoshka_test_3") sentences = [ "Teams across Delta have worked together to make an impact through enhanced landing procedures, optimizations to flight routing and speed, and weight reduction initiatives, saving over 20 million gallons of jet fuel in 2022 and 2023.", "What was the percentage increase in Services net sales from 2022 to 2023?", "How much jet fuel did Delta Air Lines save between 2022 and 2023 through optimizations in aircraft operations?", "How did Ford Pro's EBIT in 2023 compare to the previous year, and what contributed to this change?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
