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gsjang
/
kepri-embedding

Feature Extraction
Transformers
PyTorch
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use gsjang/kepri-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use gsjang/kepri-embedding with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="gsjang/kepri-embedding")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("gsjang/kepri-embedding")
    model = AutoModel.from_pretrained("gsjang/kepri-embedding")
  • Notebooks
  • Google Colab
  • Kaggle
kepri-embedding
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  • 1 contributor
History: 5 commits
NTIS's picture
NTIS
Update README.md
69863eb verified almost 2 years ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • config_setfit.json
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  • model_head.pkl

    Detected Pickle imports (4)

    • "sklearn.linear_model._logistic.LogisticRegression",
    • "numpy.ndarray",
    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "numpy.dtype"

    How to fix it?

    31.8 kB
    xet
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  • modules.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    443 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
    606 Bytes
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  • vocab.txt
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