Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
feature-extraction
Generated from Trainer
dataset_size:1363306
loss:CoSENTLoss
text-embeddings-inference
Instructions to use youssefkhalil320/all-mpnet-base-v2-pairscore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use youssefkhalil320/all-mpnet-base-v2-pairscore with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("youssefkhalil320/all-mpnet-base-v2-pairscore") sentences = [ "labneh", "iftar", "bathing suit", "coffee cup" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- 1_Pooling
- checkpoint-10500
- checkpoint-11000
- checkpoint-11500
- checkpoint-12000
- checkpoint-12500
- checkpoint-13000
- checkpoint-13500
- checkpoint-14000
- checkpoint-14500
- checkpoint-15000
- checkpoint-15500
- checkpoint-16000
- checkpoint-16500
- checkpoint-17000
- checkpoint-17500
- checkpoint-18000
- checkpoint-18500
- checkpoint-19000
- checkpoint-19500
- checkpoint-20000
- checkpoint-20500
- checkpoint-21000
- checkpoint-21302
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