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clips
/
republic

Text Classification
Transformers
PyTorch
Dutch
bert
text classification
sentiment analysis
domain adaptation
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use clips/republic with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="clips/republic")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("clips/republic")
    model = AutoModelForSequenceClassification.from_pretrained("clips/republic")
  • Notebooks
  • Google Colab
  • Kaggle
republic
437 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 36 commits
jenslemmens's picture
jenslemmens
Update README.md
bc842c6 about 3 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    2.88 kB
    Update README.md about 3 years ago
  • config.json
    857 Bytes
    add model almost 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    437 MB
    xet
    add model almost 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer almost 4 years ago
  • tokenizer.json
    473 kB
    add tokenizer almost 4 years ago
  • tokenizer_config.json
    370 Bytes
    add tokenizer almost 4 years ago
  • vocab.txt
    242 kB
    add tokenizer almost 4 years ago