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ristekcsui
/
bert-base-hs

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

Instructions to use ristekcsui/bert-base-hs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ristekcsui/bert-base-hs with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ristekcsui/bert-base-hs")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ristekcsui/bert-base-hs")
    model = AutoModel.from_pretrained("ristekcsui/bert-base-hs")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-hs
443 MB
Ctrl+K
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  • 1 contributor
History: 11 commits
widyanto's picture
widyanto
Update config.json
ccd841a over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    664 Bytes
    Update config.json over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    443 MB
    xet
    Upload pytorch_model.bin with git-lfs over 4 years ago
  • special_tokens_map.json
    112 Bytes
    Upload special_tokens_map.json over 4 years ago
  • tokenizer.json
    476 kB
    Upload tokenizer.json over 4 years ago
  • tokenizer_config.json
    379 Bytes
    Upload tokenizer_config.json over 4 years ago
  • vocab.txt
    230 kB
    Upload vocab.txt over 4 years ago