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Classical
/
Yinka

Feature Extraction
Transformers
PyTorch
bert
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
5

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

  • Libraries
  • Transformers

    How to use Classical/Yinka with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Classical/Yinka")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Classical/Yinka")
    model = AutoModel.from_pretrained("Classical/Yinka")
  • Notebooks
  • Google Colab
  • Kaggle
Yinka
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Classical's picture
Classical
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  • .gitattributes
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  • README.md
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  • config.json
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  • modules.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

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  • sentence_bert_config.json
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  • 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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