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liamcripwell
/
sle-base

Text Classification
Transformers
PyTorch
English
roberta
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use liamcripwell/sle-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="liamcripwell/sle-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("liamcripwell/sle-base")
    model = AutoModelForSequenceClassification.from_pretrained("liamcripwell/sle-base")
  • Notebooks
  • Google Colab
  • Kaggle
sle-base
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  • 1 contributor
History: 5 commits
liamcripwell's picture
liamcripwell
Update README.md
c900003 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    1.12 kB
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  • added_tokens.json
    181 Bytes
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  • config.json
    838 Bytes
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  • merges.txt
    456 kB
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  • pytorch_model.bin
    499 MB
    xet
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  • special_tokens_map.json
    957 Bytes
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  • tokenizer_config.json
    1.31 kB
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  • vocab.json
    999 kB
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