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Pranjal2002
/
all-mpnet-base-v2

Text Ranking
sentence-transformers
Safetensors
mpnet
cross-encoder
reranker
Generated from Trainer
dataset_size:3190
loss:ListNetLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Pranjal2002/all-mpnet-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Pranjal2002/all-mpnet-base-v2 with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Pranjal2002/all-mpnet-base-v2")
    
    query = "Which planet is known as the Red Planet?"
    passages = [
    	"Venus is often called Earth's twin because of its similar size and proximity.",
    	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
    	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
    ]
    
    scores = model.predict([(query, passage) for passage in passages])
    print(scores)
  • Notebooks
  • Google Colab
  • Kaggle
all-mpnet-base-v2
Ctrl+K
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  • 1 contributor
History: 2 commits
Pranjal2002's picture
Pranjal2002
Add new CrossEncoder model
f1b5488 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    16.9 kB
    Add new CrossEncoder model 8 months ago
  • config.json
    760 Bytes
    Add new CrossEncoder model 8 months ago
  • model.safetensors
    438 MB
    xet
    Add new CrossEncoder model 8 months ago
  • special_tokens_map.json
    964 Bytes
    Add new CrossEncoder model 8 months ago
  • tokenizer.json
    711 kB
    Add new CrossEncoder model 8 months ago
  • tokenizer_config.json
    1.62 kB
    Add new CrossEncoder model 8 months ago
  • vocab.txt
    232 kB
    Add new CrossEncoder model 8 months ago