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SuperSecureHuman
/
trainer_test_checkpoint

Text Classification
Transformers
PyTorch
TensorBoard
bert
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use SuperSecureHuman/trainer_test_checkpoint with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="SuperSecureHuman/trainer_test_checkpoint")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("SuperSecureHuman/trainer_test_checkpoint")
    model = AutoModelForSequenceClassification.from_pretrained("SuperSecureHuman/trainer_test_checkpoint")
  • Notebooks
  • Google Colab
  • Kaggle
trainer_test_checkpoint / checkpoint-10
1.3 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
SuperSecureHuman's picture
SuperSecureHuman
Training in progress, step 20
00879ce almost 3 years ago
  • config.json
    955 Bytes
    Training in progress, step 20 almost 3 years ago
  • optimizer.pt
    867 MB
    xet
    Training in progress, step 20 almost 3 years ago
  • pytorch_model.bin
    433 MB
    xet
    Training in progress, step 20 almost 3 years ago
  • rng_state.pth
    14.6 kB
    xet
    Training in progress, step 20 almost 3 years ago
  • scheduler.pt
    627 Bytes
    xet
    Training in progress, step 20 almost 3 years ago
  • trainer_state.json
    834 Bytes
    Training in progress, step 20 almost 3 years ago
  • training_args.bin
    3.96 kB
    xet
    Training in progress, step 20 almost 3 years ago