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amberoad
/
bert-multilingual-passage-reranking-msmarco

Text Classification
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
bert
msmarco
passage reranking
Model card Files Files and versions
xet
Community
6

Instructions to use amberoad/bert-multilingual-passage-reranking-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use amberoad/bert-multilingual-passage-reranking-msmarco with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="amberoad/bert-multilingual-passage-reranking-msmarco")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("amberoad/bert-multilingual-passage-reranking-msmarco")
    model = AutoModelForSequenceClassification.from_pretrained("amberoad/bert-multilingual-passage-reranking-msmarco")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`

#6 opened about 1 year ago by
tomaarsen

Can this model be fine-tuned? Is there any sample code for fine-tuning?

#5 opened about 2 years ago by
biaodiluer

Why is there 2 out_features in the classifier ?

➕ 1
4
#3 opened over 2 years ago by
Adovilla

Adding `safetensors` variant of this model

#2 opened about 3 years ago by
SFconvertbot
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