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jeniya
/
BERTOverflow

Feature Extraction
Transformers
PyTorch
JAX
bert
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use jeniya/BERTOverflow with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="jeniya/BERTOverflow")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("jeniya/BERTOverflow")
    model = AutoModel.from_pretrained("jeniya/BERTOverflow")
  • Notebooks
  • Google Colab
  • Kaggle
BERTOverflow
1.19 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 35 commits
patrickvonplaten's picture
patrickvonplaten
upload flax model
0361ca9 almost 5 years ago
  • .gitattributes
    391 Bytes
    allow flax almost 5 years ago
  • README.md
    1.06 kB
    Update README.md over 5 years ago
  • config.json
    3.24 kB
    Update config.json almost 6 years ago
  • flax_model.msgpack
    596 MB
    xet
    upload flax model almost 5 years ago
  • pytorch_model.bin
    596 MB
    xet
    Update pytorch_model.bin over 5 years ago
  • special_tokens_map.json
    156 Bytes
    Update special_tokens_map.json almost 6 years ago
  • tokenizer_config.json
    42 Bytes
    max_len should be 512 in tokenizer config over 5 years ago
  • vocab.txt
    660 kB
    Update vocab.txt almost 6 years ago