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Duplicated from  autoevaluate/multi-class-classification

autoevaluate
/
multi-class-classification-not-evaluated

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
2

Instructions to use autoevaluate/multi-class-classification-not-evaluated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use autoevaluate/multi-class-classification-not-evaluated with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="autoevaluate/multi-class-classification-not-evaluated")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("autoevaluate/multi-class-classification-not-evaluated")
    model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/multi-class-classification-not-evaluated")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#2 opened about 3 years ago by
SFconvertbot

Add evaluation results on the default config and test split of emotion

#1 opened over 3 years ago by
lewtun
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