Instructions to use ckiplab/bert-base-han-chinese-ws-zhonggu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/bert-base-han-chinese-ws-zhonggu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ckiplab/bert-base-han-chinese-ws-zhonggu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-han-chinese-ws-zhonggu") model = AutoModelForTokenClassification.from_pretrained("ckiplab/bert-base-han-chinese-ws-zhonggu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ckiplab/bert-base-han-chinese-ws-zhonggu: direct link, hf CLI and curl.
- Browser
- Download file 418 Bytes
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https://huggingface.co/ckiplab/bert-base-han-chinese-ws-zhonggu/resolve/main/README.md
- Command line
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hf download hf://ckiplab/bert-base-han-chinese-ws-zhonggu/README.md
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curl -L -o README.md https://huggingface.co/ckiplab/bert-base-han-chinese-ws-zhonggu/resolve/main/README.md
418 Bytes
metadata
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- bert
- zh
license: gpl-3.0
CKIP BERT Base Han Chinese WS
This model provides word segmentation for the ancient Chinese language. Our training dataset covers four eras of the Chinese language.