Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dense
Generated from Trainer
dataset_size:90177341
loss:CoSENTLoss
text-embeddings-inference
Instructions to use KhaledReda/all-MiniLM-L6-v30-pair_score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KhaledReda/all-MiniLM-L6-v30-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v30-pair_score") sentences = [ "kiprun", "fibres top", "deep plate,AbraCadabra Coral Deep Dinner Plate - Glossy White", "sun protection top" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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