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chromeNLP
/
textattack_bert_base_MNLI_fixed

Text Classification
Transformers
PyTorch
bert
Issue_fixed
textattack
textclassification
entailment
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use chromeNLP/textattack_bert_base_MNLI_fixed with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="chromeNLP/textattack_bert_base_MNLI_fixed")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("chromeNLP/textattack_bert_base_MNLI_fixed")
    model = AutoModelForSequenceClassification.from_pretrained("chromeNLP/textattack_bert_base_MNLI_fixed")
  • Notebooks
  • Google Colab
  • Kaggle
textattack_bert_base_MNLI_fixed
439 MB
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  • 1 contributor
History: 6 commits
chromeNLP's picture
chromeNLP
Update README.md
c18455a over 3 years ago
  • .gitattributes
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  • README.md
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  • config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch.LongStorage"

    What is a pickle import?

    438 MB
    xet
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  • special_tokens_map.json
    112 Bytes
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.txt
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