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pujithapsx
/
test

Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:147
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use pujithapsx/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use pujithapsx/test with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("pujithapsx/test")
    
    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
test
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
pujithapsx's picture
pujithapsx
LoRA fine-tune – full record entity matching
716ed09 verified about 1 month ago
  • .gitattributes
    1.57 kB
    LoRA fine-tune – full record entity matching about 1 month ago
  • README.md
    38.1 kB
    LoRA fine-tune – full record entity matching about 1 month ago
  • config.json
    873 Bytes
    LoRA fine-tune – full record entity matching about 1 month ago
  • model.safetensors
    2.27 GB
    xet
    LoRA fine-tune – full record entity matching about 1 month ago
  • special_tokens_map.json
    964 Bytes
    LoRA fine-tune – full record entity matching about 1 month ago
  • tokenizer.json
    17.1 MB
    xet
    LoRA fine-tune – full record entity matching about 1 month ago
  • tokenizer_config.json
    1.2 kB
    LoRA fine-tune – full record entity matching about 1 month ago