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gefgu
/
modernbert-activity-aligner

Text Ranking
sentence-transformers
Safetensors
modernbert
cross-encoder
reranker
Generated from Trainer
dataset_size:5000
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use gefgu/modernbert-activity-aligner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use gefgu/modernbert-activity-aligner with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("gefgu/modernbert-activity-aligner")
    
    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
modernbert-activity-aligner
602 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
gefgu's picture
gefgu
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  • .gitattributes
    1.52 kB
    initial commit 16 days ago
  • README.md
    18.5 kB
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  • config.json
    1.3 kB
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  • config_sentence_transformers.json
    261 Bytes
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  • model.safetensors
    598 MB
    xet
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  • modules.json
    131 Bytes
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  • sentence_bert_config.json
    225 Bytes
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  • special_tokens_map.json
    694 Bytes
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  • tokenizer.json
    3.58 MB
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  • tokenizer_config.json
    20.8 kB
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