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jamescalam
/
bert-base-dv

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

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

  • Libraries
  • Transformers

    How to use jamescalam/bert-base-dv with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="jamescalam/bert-base-dv")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("jamescalam/bert-base-dv")
    model = AutoModelForMaskedLM.from_pretrained("jamescalam/bert-base-dv")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-dv
267 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
jamescalam's picture
jamescalam
new model pretrained for 2 epochs
bc4c003 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    776 Bytes
    add to readme over 4 years ago
  • config.json
    588 Bytes
    pretrained on full dhivehi data over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    266 MB
    xet
    new model pretrained for 2 epochs over 4 years ago
  • special_tokens_map.json
    112 Bytes
    first model iteration (do not use) over 4 years ago
  • tokenizer.json
    678 kB
    pretrained on full dhivehi data over 4 years ago
  • tokenizer_config.json
    158 Bytes
    first model iteration (do not use) over 4 years ago