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Reproducibility
/
naacl22_causalDistilBERT_instance_3

Fill-Mask
Transformers
PyTorch
distilbert
Model card Files Files and versions
xet
Community
1

Instructions to use Reproducibility/naacl22_causalDistilBERT_instance_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Reproducibility/naacl22_causalDistilBERT_instance_3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="Reproducibility/naacl22_causalDistilBERT_instance_3")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("Reproducibility/naacl22_causalDistilBERT_instance_3")
    model = AutoModelForMaskedLM.from_pretrained("Reproducibility/naacl22_causalDistilBERT_instance_3", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
naacl22_causalDistilBERT_instance_3
1.22 kB
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  • 1 contributor
History: 1 commit
zhengxuanzenwu's picture
zhengxuanzenwu
initial commit
8a20ec8 over 4 years ago
  • .gitattributes
    1.22 kB
    initial commit over 4 years ago