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microsoft
/
deberta-base-mnli

Text Classification
Transformers
PyTorch
Rust
English
deberta
deberta-v1
deberta-mnli
Model card Files Files and versions
xet
Community
1

Instructions to use microsoft/deberta-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/deberta-base-mnli with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="microsoft/deberta-base-mnli")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-base-mnli")
    model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-base-mnli")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
deberta-base-mnli
1.12 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 17 commits
guillaume-be's picture
guillaume-be
Addition of Rust model
a80a6eb over 4 years ago
  • .gitattributes
    690 Bytes
    initial commit over 5 years ago
  • README.md
    1.44 kB
    Update README.md almost 5 years ago
  • bpe_encoder.bin

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    3.92 MB
    xet
    Create deberta base mnli fine-tuned model over 5 years ago
  • config.json
    728 Bytes
    Add task config about 5 years ago
  • merges.txt
    456 kB
    Add gpt vocab about 5 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    557 MB
    xet
    Create deberta base mnli fine-tuned model over 5 years ago
  • rust_model.ot
    557 MB
    xet
    Addition of Rust model over 4 years ago
  • tokenizer_config.json
    52 Bytes
    Add vocab type config over 5 years ago
  • vocab.json
    899 kB
    Add gpt vocab about 5 years ago