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Duplicated from聽 autoevaluate/extractive-question-answering

autoevaluate
/
extractive-question-answering-not-evaluated

Question Answering
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
4

Instructions to use autoevaluate/extractive-question-answering-not-evaluated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use autoevaluate/extractive-question-answering-not-evaluated with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="autoevaluate/extractive-question-answering-not-evaluated")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("autoevaluate/extractive-question-answering-not-evaluated")
    model = AutoModelForQuestionAnswering.from_pretrained("autoevaluate/extractive-question-answering-not-evaluated")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Librarian Bot: Add base_model information to model

#4 opened over 2 years ago by
librarian-bot

Adding `safetensors` variant of this model

#3 opened about 3 years ago by
SFconvertbot

Add evaluation results on the autoevaluate--squad-sample config and test split of autoevaluate/squad-sample

#2 opened over 3 years ago by
autoevaluator

Add evaluation results on the autoevaluate--squad-sample config and test split of autoevaluate/squad-sample

#1 opened over 3 years ago by
lewtun
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