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abletobetable
/
stress_bert

Text Classification
Transformers
PyTorch
distilbert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use abletobetable/stress_bert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="abletobetable/stress_bert")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("abletobetable/stress_bert")
    model = AutoModelForSequenceClassification.from_pretrained("abletobetable/stress_bert")
  • Notebooks
  • Google Colab
  • Kaggle
stress_bert
25.9 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
abletobetable's picture
abletobetable
Training in progress, step 5600
2debdcb about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 400 about 3 years ago
  • config.json
    907 Bytes
    Training in progress, step 400 about 3 years ago
  • pytorch_model.bin
    25.9 MB
    xet
    Training in progress, step 5600 about 3 years ago
  • special_tokens_map.json
    27 Bytes
    Training in progress, step 400 about 3 years ago
  • tokenizer.json
    16.1 kB
    Training in progress, step 400 about 3 years ago
  • tokenizer_config.json
    146 Bytes
    Training in progress, step 400 about 3 years ago
  • training_args.bin
    3.58 kB
    xet
    Training in progress, step 400 about 3 years ago