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horsbug98
/
Part_2_mBERT_Model_E2

Question Answering
Transformers
PyTorch
bert
Generated from Trainer
Model card Files Files and versions
xet
Community
2

Instructions to use horsbug98/Part_2_mBERT_Model_E2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use horsbug98/Part_2_mBERT_Model_E2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="horsbug98/Part_2_mBERT_Model_E2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_2_mBERT_Model_E2")
    model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_2_mBERT_Model_E2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Part_2_mBERT_Model_E2
717 MB
Ctrl+K
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  • 1 contributor
History: 16 commits
horsbug98's picture
horsbug98
Upload pytorch_model.bin with git-lfs
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  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    1.09 kB
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  • all_results.json
    297 Bytes
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  • config.json
    841 Bytes
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  • eval_nbest_predictions.json
    4.59 MB
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  • eval_predictions.json
    77.7 kB
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  • eval_results.json
    122 Bytes
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  • pytorch_model.bin
    709 MB
    xet
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  • special_tokens_map.json
    112 Bytes
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  • tokenizer.json
    1.96 MB
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  • tokenizer_config.json
    333 Bytes
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  • train_results.json
    195 Bytes
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  • trainer_state.json
    1.08 kB
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  • training_args.bin
    2.99 kB
    xet
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  • vocab.txt
    996 kB
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