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breadlicker45
/
test-class

Text Classification
Transformers
PyTorch
distilbert
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use breadlicker45/test-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use breadlicker45/test-class with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="breadlicker45/test-class")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("breadlicker45/test-class")
    model = AutoModelForSequenceClassification.from_pretrained("breadlicker45/test-class", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
test-class
269 MB
Ctrl+K
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  • 3 contributors
History: 9 commits
breadlicker45's picture
breadlicker45
Upload 7 files
77c9b7a about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • added_tokens.json
    77 Bytes
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  • config.json
    690 Bytes
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  • optimizer.pt
    819 Bytes
    xet
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  • pytorch_model.bin
    268 MB
    xet
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  • rng_state.pth
    14.6 kB
    xet
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  • scaler.pt
    557 Bytes
    xet
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  • scheduler.pt
    627 Bytes
    xet
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  • special_tokens_map.json
    193 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    388 Bytes
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  • trainer_state.json
    529 kB
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  • training_args.bin
    3.9 kB
    xet
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  • vocab.txt
    232 kB
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