Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:574
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use Ananthu357/Ananthus-BAAI-for-contracts7.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ananthu357/Ananthus-BAAI-for-contracts7.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ananthu357/Ananthus-BAAI-for-contracts7.0") sentences = [ "What is mentioned regarding the patent errors?", "the Schedule to the Indian Medical Council Act", "shall take upon himself and provide for the risk of any error which may subsequently be discovered and shall make no subsequent claim on account thereof.", "Omissions and Descrepancies" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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