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vaibhav9
/
hangman-bert-base

Fill-Mask
Transformers
PyTorch
bert
Generated from Trainer
Model card Files Files and versions
xet
Community
1

Instructions to use vaibhav9/hangman-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use vaibhav9/hangman-bert-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="vaibhav9/hangman-bert-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("vaibhav9/hangman-bert-base")
    model = AutoModelForMaskedLM.from_pretrained("vaibhav9/hangman-bert-base", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
hangman-bert-base
438 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
vaibhav9's picture
vaibhav9
End of training
00087ba almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    1.38 kB
    End of training almost 3 years ago
  • config.json
    664 Bytes
    End of training almost 3 years ago
  • generation_config.json
    90 Bytes
    End of training almost 3 years ago
  • pytorch_model.bin
    438 MB
    xet
    End of training almost 3 years ago
  • training_args.bin
    4.03 kB
    xet
    End of training almost 3 years ago