Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:2400000
loss:CoSENTLoss
text-embeddings-inference
Instructions to use youssefkhalil320/all-MiniLM-L6-v9-pair_score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use youssefkhalil320/all-MiniLM-L6-v9-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("youssefkhalil320/all-MiniLM-L6-v9-pair_score") sentences = [ "poolside pants", "safe materials toy", "plated necklace", "washed cargo pants" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- 1_Pooling
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