Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:6300
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sintuk/bge-base-financial-matryoshka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sintuk/bge-base-financial-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sintuk/bge-base-financial-matryoshka") sentences = [ "As of December 30, 2023, about 92% of securities in the Company's portfolio were at an unrealized loss position.", "What additional document is included in the financial document apart from the Consolidated Financial Statements?", "What percentage of the Company's portfolio of securities was in an unrealized loss position as of December 30, 2023?", "What was the total loss the company incurred in association with the sale of the eOne Music business in 2021?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle