Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
Generated from Trainer
dataset_size:3692
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use calvin2258000/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use calvin2258000/test2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("calvin2258000/test2") sentences = [ "| :-- | :--: | :--: || After the coming into force date | 1.00 | 1.00 || 6 April 2014 - coming into force date | 1.30 | 1.30 || 1 Oct 2010 - 5 April 2014 | 1.40 | 1.40 || 6 April 2006 - 30 Sept 2010 | 1.67 | 1.67 || Pre 6 April 2006 | 1.67 | 1.67 |", "What are the applicable building regulation change factors for different time periods starting from pre-6 April 2006 to the current date?", "When are protected lobbies or corridors required for staircases in buildings with multiple storeys above ground level?", "What are the standards for repairing, reconstructing, and altering existing drains and sewers?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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