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BEE-spoke-data
/
neobert-100k-test

Fill-Mask
Transformers
PyTorch
Safetensors
English
neobert
custom_code
Model card Files Files and versions
xet
Community

Instructions to use BEE-spoke-data/neobert-100k-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BEE-spoke-data/neobert-100k-test with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="BEE-spoke-data/neobert-100k-test", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("BEE-spoke-data/neobert-100k-test", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
neobert-100k-test
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  • 1 contributor
History: 1 commit
pszemraj's picture
pszemraj
Super-squash branch 'main' using huggingface_hub
a07e32a verified 5 months ago
  • .gitattributes
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  • README.md
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  • config.json
    625 Bytes
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  • model.py
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  • model.safetensors
    537 MB
    xet
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    537 MB
    xet
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  • rotary.py
    2.58 kB
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  • special_tokens_map.json
    971 Bytes
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  • tokenizer.json
    782 kB
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  • tokenizer_config.json
    1.32 kB
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