Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dense
Generated from Trainer
dataset_size:27697700
loss:CoSENTLoss
text-embeddings-inference
Instructions to use KhaledReda/all-MiniLM-L6-v65-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-v65-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v65-pair_score") sentences = [ "vee melatonin 10tab", "keto hot dog keto saucisse", "yoga brick grey yoga brick foam yoga brick lightweight yoga brick pilates brick aerobics brick keep this yoga accessory to make your training more challenging everyday. the yoga brick is suitable for all kinds of ground-based fitness exercises such as pilates and aerobics besides yoga. designed to increase flexibility improves alignment for deepening and elongate your stretches. lightweight high density and sturdy foam for durability.", "goddess bodysuit - silver shimmer metallic bodysuit shimmer silver bodysuit effortless glamour in our bodysuit goddess . model size s. material elastane lycra and metallic fabric. share." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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