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z-uo
/
bert-qasper

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

Instructions to use z-uo/bert-qasper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use z-uo/bert-qasper with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="z-uo/bert-qasper")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("z-uo/bert-qasper")
    model = AutoModelForQuestionAnswering.from_pretrained("z-uo/bert-qasper")
  • Notebooks
  • Google Colab
  • Kaggle
bert-qasper
Ctrl+K
Ctrl+K
  • 2 contributors
History: 6 commits
z-uo's picture
z-uo
Update README.md
cf52cce about 4 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • README.md
    2.14 kB
    Update README.md about 4 years ago
  • all_results.json
    194 Bytes
    train results without checkpoints about 4 years ago
  • config.json
    678 Bytes
    train results without checkpoints about 4 years ago
  • pytorch_model.bin
    436 MB
    xet
    train results without checkpoints about 4 years ago
  • special_tokens_map.json
    112 Bytes
    train results without checkpoints about 4 years ago
  • tokenizer.json
    712 kB
    train results without checkpoints about 4 years ago
  • tokenizer_config.json
    321 Bytes
    train results without checkpoints about 4 years ago
  • train_results.json
    194 Bytes
    train results without checkpoints about 4 years ago
  • trainer_state.json
    2.3 kB
    train results without checkpoints about 4 years ago
  • training_args.bin
    3.06 kB
    xet
    train results without checkpoints about 4 years ago
  • vocab.txt
    232 kB
    train results without checkpoints about 4 years ago