Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:281362
loss:CachedMultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use spl4shedEdu/mpnet_ISB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use spl4shedEdu/mpnet_ISB with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("spl4shedEdu/mpnet_ISB") sentences = [ "steel lock washer 8 x 144 2 mm zinc plated split 2004 bmw 325ci base convertible miscellaneous hardware page 3 auveco 17397m769 automotive", "steel lock washer 8 x 144 2 mm zinc plated split 1993 bmw 318i base sedan miscellaneous hardware page 3 auveco 17397m769 automotive", "generac protector rg03624ansx standby generators liquidcooled reviews ratings product discontinued discontinued electric directcom 696471617450 toolsandhomeimprovement", "drive belt tensioner water pumpalternator 1994 bmw 325i base convertible charging system battery page 6 note shock type hydraulic ina 11281717188m40 automotive" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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