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inovex
/
multi2convai-quality-de-bert

Text Classification
Transformers
PyTorch
German
bert
Model card Files Files and versions
xet
Community
1

Instructions to use inovex/multi2convai-quality-de-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use inovex/multi2convai-quality-de-bert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="inovex/multi2convai-quality-de-bert")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("inovex/multi2convai-quality-de-bert")
    model = AutoModelForSequenceClassification.from_pretrained("inovex/multi2convai-quality-de-bert")
  • Notebooks
  • Google Colab
  • Kaggle
multi2convai-quality-de-bert
440 MB
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  • 1 contributor
History: 5 commits
sblank's picture
sblank
Update readme
969f8fb over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    965 Bytes
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  • config.json
    2.19 kB
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  • label_dict.json
    678 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    440 MB
    xet
    Add label dict and model over 4 years ago
  • special_tokens_map.json
    112 Bytes
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  • tokenizer_config.json
    49 Bytes
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  • vocab.txt
    240 kB
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