Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dense
Generated from Trainer
dataset_size:24797767
loss:CoSENTLoss
text-embeddings-inference
Instructions to use KhaledReda/all-MiniLM-L6-v77-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-v77-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v77-pair_score") sentences = [ "rehydro-zinc 10sachnew", "ramadan giveaway bag 6 pieces", "skittles - crazy sours - 160 gr candy crazy sours candy skittles candy crazy sours cande crazy sours nan", "mask face reusable textile pink nile face mask reusable face mask textile face mask" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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