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 NickyNicky/bge-base-financial-matryoshka_test_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NickyNicky/bge-base-financial-matryoshka_test_1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NickyNicky/bge-base-financial-matryoshka_test_1") sentences = [ "Item 3—Legal Proceedings See discussion of Legal Proceedings in Note 10 to the consolidated financial statements included in Item 8 of this Report.", "What financial measures are presented on a non-GAAP basis in this Annual Report on Form 10-K?", "Which section of the report discusses Legal Proceedings?", "What criteria was used to audit the internal control over financial reporting of The Procter & Gamble Company as of June 30, 2023?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K