Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:623
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use Ananthu357/Ananthus-BAAI-for-contracts9.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ananthu357/Ananthus-BAAI-for-contracts9.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ananthu357/Ananthus-BAAI-for-contracts9.0") sentences = [ "Contractor shall be liable to pay the actual expenses incurred in measurements.", "Does the contract contain a 'third party liability relations' clause?", "Does the contract contain a 'third party liability relations' clause?", "The additional documents to be referred are attached as annex to the tender forms." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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