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 JulioSanchezD/bge-base-financial-matryoshka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JulioSanchezD/bge-base-financial-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JulioSanchezD/bge-base-financial-matryoshka") sentences = [ "The Health Services segment's revenues are primarily generated from the sale and managing of prescription drugs to eligible members in benefit plans maintained by clients.", "What online platforms does The Home Depot operate for its product offerings?", "How does the Company's Health Services segment generate most of its revenue?", "What are the various diversity, equity, and inclusion councils at AMC?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K