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Shularp
/
finetuned-bert-mrpc

Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
2

Instructions to use Shularp/finetuned-bert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Shularp/finetuned-bert-mrpc with Transformers:

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

Adding `safetensors` variant of this model

#2 opened about 1 year ago by
SFconvertbot

Librarian Bot: Add base_model information to model

#1 opened over 2 years ago by
librarian-bot
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