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routellm
/
bert_mmlu_augmented

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

Instructions to use routellm/bert_mmlu_augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use routellm/bert_mmlu_augmented with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="routellm/bert_mmlu_augmented")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("routellm/bert_mmlu_augmented")
    model = AutoModelForSequenceClassification.from_pretrained("routellm/bert_mmlu_augmented")
  • Notebooks
  • Google Colab
  • Kaggle
bert_mmlu_augmented
3.36 GB
Ctrl+K
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  • 1 contributor
History: 3 commits
iojw's picture
iojw
Create LICENSE
7c34ac7 verified about 1 year ago
  • .gitattributes
    1.57 kB
    Add MMLU BERT almost 2 years ago
  • LICENSE
    11.4 kB
    Create LICENSE about 1 year ago
  • config.json
    924 Bytes
    Add MMLU BERT almost 2 years ago
  • model.safetensors
    1.11 GB
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  • optimizer.pt
    2.22 GB
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  • rng_state.pth
    14.2 kB
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  • scheduler.pt
    1.06 kB
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  • sentencepiece.bpe.model
    5.07 MB
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    Add MMLU BERT almost 2 years ago
  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.15 kB
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  • trainer_state.json
    755 Bytes
    Add MMLU BERT almost 2 years ago
  • training_args.bin
    5.05 kB
    xet
    Add MMLU BERT almost 2 years ago