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KoichiYasuoka
/
roberta-classical-chinese-base-sentence-segmentation

Token Classification
Transformers
PyTorch
Literary Chinese
roberta
classical chinese
literary chinese
ancient chinese
sentence segmentation
Model card Files Files and versions
xet
Community
6

Instructions to use KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation")
    model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
roberta-classical-chinese-base-sentence-segmentation
423 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 18 commits
KoichiYasuoka's picture
KoichiYasuoka
base_model
92f39c1 almost 2 years ago
  • .gitattributes
    737 Bytes
    initial commit almost 5 years ago
  • README.md
    1.7 kB
    base_model almost 2 years ago
  • config.json
    890 Bytes
    "O" -> "M" almost 5 years ago
  • pytorch_model.bin
    423 MB
    xet
    initial release almost 5 years ago
  • special_tokens_map.json
    112 Bytes
    initial release almost 5 years ago
  • tokenizer_config.json
    297 Bytes
    model_max_length almost 5 years ago
  • vocab.txt
    106 kB
    initial release almost 5 years ago