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howey
/
bert-base-uncased-squad-L6

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

Instructions to use howey/bert-base-uncased-squad-L6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use howey/bert-base-uncased-squad-L6 with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "question-answering" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # pip install "transformers<5.0.0"
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="howey/bert-base-uncased-squad-L6")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("howey/bert-base-uncased-squad-L6")
    model = AutoModelForQuestionAnswering.from_pretrained("howey/bert-base-uncased-squad-L6", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-uncased-squad-L6
531 MB
Ctrl+K
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  • 2 contributors
History: 4 commits
patrickvonplaten's picture
patrickvonplaten
upload flax model
7df8923 over 5 years ago
  • .gitattributes
    391 Bytes
    allow flax over 5 years ago
  • config.json
    627 Bytes
    submit L6 almost 6 years ago
  • flax_model.msgpack
    265 MB
    xet
    upload flax model over 5 years ago
  • pytorch_model.bin
    266 MB
    xet
    submit L6 almost 6 years ago
  • special_tokens_map.json
    112 Bytes
    submit L6 almost 6 years ago
  • tokenizer_config.json
    433 Bytes
    submit L6 almost 6 years ago
  • training_args.bin
    2.29 kB
    xet
    submit L6 almost 6 years ago
  • vocab.txt
    232 kB
    submit L6 almost 6 years ago