Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:368
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use Ananthu357/Ananthus-BAAI-for-contracts3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ananthu357/Ananthus-BAAI-for-contracts3.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ananthu357/Ananthus-BAAI-for-contracts3.0") sentences = [ "These Standard General Conditions of Contract can be altered by Special Conditions of Contract included in the Tender Forms.", "The clause defines Order of Precedence very well.", "Does the contract contain a 'third party liability relations' clause?", " Special Conditions can modify the Standard General Conditions." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle