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NeginShams
/
cross_encoder_v2

Text Classification
Transformers
Safetensors
xlm-roberta
cross-encoder
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use NeginShams/cross_encoder_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NeginShams/cross_encoder_v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="NeginShams/cross_encoder_v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("NeginShams/cross_encoder_v2")
    model = AutoModelForSequenceClassification.from_pretrained("NeginShams/cross_encoder_v2")
  • Notebooks
  • Google Colab
  • Kaggle
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Update model metadata to set pipeline tag to the new `text-ranking` and tags to `sentence-transformers`

#1 opened about 1 year ago by
tomaarsen
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