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QQhahaha
/
QuestionAnswering

Question Answering
Transformers
PyTorch
Chinese
bert
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use QQhahaha/QuestionAnswering with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="QQhahaha/QuestionAnswering")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("QQhahaha/QuestionAnswering")
    model = AutoModelForQuestionAnswering.from_pretrained("QQhahaha/QuestionAnswering")
  • Notebooks
  • Google Colab
  • Kaggle
QuestionAnswering
2.61 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
489d99f verified over 1 year ago
  • .gitattributes
    1.58 kB
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  • README.md
    2.13 kB
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  • all_results.json
    79 Bytes
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  • config.json
    911 Bytes
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  • eval_nbest_predictions.json
    14.1 MB
    xet
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  • eval_predictions.json
    214 kB
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  • model.safetensors
    1.3 GB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • pytorch_model.bin
    1.3 GB
    xet
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    439 kB
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  • tokenizer_config.json
    497 Bytes
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  • vocab.txt
    110 kB
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