How to use ethan-ky/bge-base-financial-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ethan-ky/bge-base-financial-matryoshka") sentences = [ "As of January 31, 2023, the weighted average remaining lease term for operating leases was 7 years and for finance leases was 3 years.", "What was the Company's net deferred tax assets as of December 30, 2023, and December 31, 2022?", "What were the weighted average remaining lease terms for operating and finance leases as of January 31, 2023?", "How much did the net investment income change from 2021 to 2023?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
