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not-lain
/
test-dynamic-pipeline

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

Instructions to use not-lain/test-dynamic-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use not-lain/test-dynamic-pipeline with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="not-lain/test-dynamic-pipeline")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("not-lain/test-dynamic-pipeline")
    model = AutoModelForSequenceClassification.from_pretrained("not-lain/test-dynamic-pipeline")
  • Notebooks
  • Google Colab
  • Kaggle
test-dynamic-pipeline
779 kB
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  • 2 contributors
History: 6 commits
not-lain's picture
not-lain
Update README.md
d674bd3 verified over 2 years ago
  • .gitattributes
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  • README.md
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  • config.json
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  • custom_pipeline.py
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  • model.safetensors
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    384 kB
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    commit files to HF hub almost 4 years ago
  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.txt
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