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Hartunka
/
bert_base_rand_20_v1_mrpc

Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use Hartunka/bert_base_rand_20_v1_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Hartunka/bert_base_rand_20_v1_mrpc with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Hartunka/bert_base_rand_20_v1_mrpc")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_rand_20_v1_mrpc")
    model = AutoModelForSequenceClassification.from_pretrained("Hartunka/bert_base_rand_20_v1_mrpc")
  • Notebooks
  • Google Colab
  • Kaggle
bert_base_rand_20_v1_mrpc / logs
10.2 kB
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  • 1 contributor
History: 4 commits
Hartunka's picture
Hartunka
End of training
8a46496 verified about 1 year ago
  • events.out.tfevents.1745147380.s_005_m.2796520.74
    9.73 kB
    xet
    Model save about 1 year ago
  • events.out.tfevents.1745147459.s_005_m.2796520.75
    459 Bytes
    xet
    End of training about 1 year ago