Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:132
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Areeb-02/bge-large-en-v1.5-CosentLoss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Areeb-02/bge-large-en-v1.5-CosentLoss with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Areeb-02/bge-large-en-v1.5-CosentLoss") sentences = [ "A person shall have 3045 days after commencing business within the City to apply for a registration certificate.", "The new transportation plan replaces the previous one approved by San Francisco voters in 2003. |", "The Department of Elections is revising sections of its definitions and deleting a section to operate definitions for Article 12. |", "A newly-established business shall have 3045 days after commencing business within the City to apply for a registration certificate, and the registration fee for such businesses shall be prorated based on the estimated gross receipts for the tax year in which the business commences." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K