Token Classification
Transformers
PyTorch
Literary Chinese
roberta
classical chinese
literary chinese
ancient chinese
sentence segmentation
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
Commit ·
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Parent(s): 88ff112
sentence segmentation
Browse files
README.md
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- "classical chinese"
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- "literary chinese"
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- "ancient chinese"
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- "token-classification"
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license: "apache-2.0"
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pipeline_tag: "token-classification"
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- "classical chinese"
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- "literary chinese"
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- "ancient chinese"
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- "sentence segmentation"
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- "token-classification"
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license: "apache-2.0"
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pipeline_tag: "token-classification"
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