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philschmid
/
BERT-Banking77

Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
5

Instructions to use philschmid/BERT-Banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use philschmid/BERT-Banking77 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="philschmid/BERT-Banking77")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("philschmid/BERT-Banking77")
    model = AutoModelForSequenceClassification.from_pretrained("philschmid/BERT-Banking77")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#5 opened about 3 years ago by
SFconvertbot

Add evaluation results on the default config and test split of banking77

#3 opened over 3 years ago by
autoevaluator
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