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hfl
/
chinese-macbert-large

Fill-Mask
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
Chinese
bert
Model card Files Files and versions
xet

Instructions to use hfl/chinese-macbert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hfl/chinese-macbert-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="hfl/chinese-macbert-large")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-macbert-large")
    model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-macbert-large")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
chinese-macbert-large
4 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 14 commits
patrickvonplaten's picture
patrickvonplaten
upload flax model
1cf2677 almost 5 years ago
  • .gitattributes
    391 Bytes
    allow flax almost 5 years ago
  • README.md
    3.84 kB
    Update README.md over 5 years ago
  • added_tokens.json
    2 Bytes
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  • config.json
    660 Bytes
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  • flax_model.msgpack
    1.3 GB
    xet
    upload flax model almost 5 years ago
  • pytorch_model.bin
    1.31 GB
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  • special_tokens_map.json
    112 Bytes
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  • tf_model.h5
    1.4 GB
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  • tokenizer.json
    269 kB
    add fast tokenizer config about 5 years ago
  • tokenizer_config.json
    19 Bytes
    Update tokenizer_config.json over 5 years ago
  • vocab.txt
    110 kB
    Update vocab.txt over 5 years ago