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subhasisj
/
Ar-Mulitlingula-MiniLM

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

Instructions to use subhasisj/Ar-Mulitlingula-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use subhasisj/Ar-Mulitlingula-MiniLM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="subhasisj/Ar-Mulitlingula-MiniLM")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("subhasisj/Ar-Mulitlingula-MiniLM")
    model = AutoModelForMaskedLM.from_pretrained("subhasisj/Ar-Mulitlingula-MiniLM", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Ar-Mulitlingula-MiniLM
472 MB
Ctrl+K
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  • 1 contributor
History: 7 commits
subhasisj's picture
subhasisj
Create README.md
a861604 over 4 years ago
  • .gitattributes
    1.17 kB
    initial commit over 4 years ago
  • README.md
    674 Bytes
    Create README.md over 4 years ago
  • config.json
    695 Bytes
    Upload config.json over 4 years ago
  • gitattributes
    1.17 kB
    Upload gitattributes over 4 years ago
  • gitignore
    13 Bytes
    Upload gitignore over 4 years ago
  • pytorch_model.bin
    472 MB
    xet
    Upload pytorch_model.bin with git-lfs over 4 years ago
  • training_args.bin
    3.12 kB
    xet
    Upload training_args.bin with git-lfs over 4 years ago