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jgonik
/
nlp-puzzle

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

Instructions to use jgonik/nlp-puzzle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jgonik/nlp-puzzle with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="jgonik/nlp-puzzle")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("jgonik/nlp-puzzle")
    model = AutoModelForSequenceClassification.from_pretrained("jgonik/nlp-puzzle")
  • Notebooks
  • Google Colab
  • Kaggle
nlp-puzzle
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Julia Gonik
add tokenizer
28c3cbb almost 5 years ago
  • .gitattributes
    737 Bytes
    initial commit almost 5 years ago
  • config.json
    695 Bytes
    add model almost 5 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    17.6 MB
    xet
    add model almost 5 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer almost 5 years ago
  • tokenizer.json
    466 kB
    add tokenizer almost 5 years ago
  • tokenizer_config.json
    346 Bytes
    add tokenizer almost 5 years ago
  • vocab.txt
    232 kB
    add tokenizer almost 5 years ago