Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dense
Generated from Trainer
dataset_size:24801118
loss:CoSENTLoss
text-embeddings-inference
Instructions to use KhaledReda/all-MiniLM-L6-v74-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-v74-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v74-pair_score") sentences = [ "stainless steel scissors", "diy cake set detachable cake toy safe oil based paints toy diy cake toy set toy the cake set is an educational and designed to stimulate creativity and develop fine motor skills in children through the experience of making and decorating cakes with various colors and shapes. the set includes a three-dimensional detachable cake mold a selection of safe oil-based paints paintbrushes and decorating tools that allow children to design and color the cake according to their imagination. this makes it an exceptional educational experience for learning colors and developing artistic sensibilities. features creativity enhancement allows children to design and decorate cakes with different colors and shapes boosting their imagination and creativit", "lissio light radiance cr 50m light radiance cream lissio light radiance cream", "mocha latte bottle coffee" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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