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achadj
/
footballbert-base

Fill-Mask
Transformers
Safetensors
English
footballbert
football
soccer
sports-analytics
player-embeddings
custom_code
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use achadj/footballbert-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="achadj/footballbert-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("achadj/footballbert-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
footballbert-base
231 MB
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  • 1 contributor
History: 52 commits
achadj's picture
achadj
Update README.md
2f9107d verified 7 months ago
  • .gitattributes
    1.57 kB
    Upload footballbert.png 7 months ago
  • README.md
    13.7 kB
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  • __init__.py
    593 Bytes
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  • added_tokens.json
    44 Bytes
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  • baller_id2player_names_99316p.pkl

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    2.77 MB
    xet
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  • config.json
    790 Bytes
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  • configuration_footballbert.py
    3.62 kB
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  • footballbert.png
    520 kB
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  • model.safetensors
    226 MB
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  • modeling_footballbert.py
    14.4 kB
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  • player_vocab.json
    2.19 MB
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  • position_vocab.json
    188 Bytes
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  • season_vocab.json
    398 Bytes
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  • special_tokens_map.json
    134 Bytes
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  • tokenization_footballbert.py
    12.2 kB
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  • tokenizer_config.json
    719 Bytes
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