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facebook
/
xmod-base

Fill-Mask
Transformers
PyTorch
xmod
Model card Files Files and versions
xet
Community
3

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

  • Libraries
  • Transformers

    How to use facebook/xmod-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="facebook/xmod-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("facebook/xmod-base")
    model = AutoModelForMaskedLM.from_pretrained("facebook/xmod-base")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
xmod-base
3.42 GB
Ctrl+K
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  • 2 contributors
History: 9 commits
lysandre's picture
lysandre HF Staff
jvamvas's picture
jvamvas
Add XLM-R tokenizer files (#2)
1ff2383 over 2 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    9.02 kB
    Add XLM-R tokenizer files (#2) over 2 years ago
  • config.json
    1.83 kB
    Remove "classifier_dropout": null about 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    3.41 GB
    xet
    Upload model over 3 years ago
  • tokenizer.json
    9.1 MB
    Add XLM-R tokenizer files (#2) over 2 years ago
  • tokenizer_config.json
    48 Bytes
    Add XLM-R tokenizer files (#2) over 2 years ago