Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:207
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use Ananthu357/BAAI-first-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ananthu357/BAAI-first-train with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ananthu357/BAAI-first-train") sentences = [ "What are the additional documents that have to be read along with the Standard General Conditions of Contract?", " Nothing stated herein shall preclude the Contractor in achieving earlier completion of item or whole of the works than indicated in the programme.", "These Regulations for Tenders and Contracts shall be read in conjunction with the Standard General Conditions of Contract which are referred to herein and shall be subject to modifications additions or suppression by Special Conditions of Contract and/or Special Specifications, if any, annexed to the Tender Forms.", "Does the contract contain a 'third party liability relations' clause?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit History
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Add new SentenceTransformer model.
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