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DreamingRabbit
/
CPGen-difficulty-classification

Text Classification
Transformers
Safetensors
modernbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use DreamingRabbit/CPGen-difficulty-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DreamingRabbit/CPGen-difficulty-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="DreamingRabbit/CPGen-difficulty-classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("DreamingRabbit/CPGen-difficulty-classification")
    model = AutoModelForSequenceClassification.from_pretrained("DreamingRabbit/CPGen-difficulty-classification")
  • Notebooks
  • Google Colab
  • Kaggle
CPGen-difficulty-classification
4.75 GB
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  • 1 contributor
History: 2 commits
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  • .gitattributes
    1.52 kB
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  • README.md
    336 Bytes
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  • config.json
    1.7 kB
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  • model.safetensors
    1.58 GB
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  • optimizer.pt
    3.17 GB
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  • rng_state.pth
    14.6 kB
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  • scheduler.pt
    1.47 kB
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  • special_tokens_map.json
    694 Bytes
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  • tokenizer.json
    3.58 MB
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  • tokenizer_config.json
    20.9 kB
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  • trainer_state.json
    774 Bytes
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  • training_args.bin
    6.03 kB
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  • upload.py
    413 Bytes
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