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- # CKIP ALBERT Base Chinese — Named-Entity Recognition
 
 
 
 
 
 
 
 
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  ## Contributers
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  * [Mu Yang](https://muyang.pro) at [CKIP](https://ckip.iis.sinica.edu.tw) (Author & Maintainer)
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- ## Attention
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- Please Use `BertTokenizer` instead of `AutoTokenizer`!!!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  metrics:
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+ # CKIP ALBERT Base Chinese
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+ This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segmentation, part-of-speech tagging, named entity recognition).
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+ 這個專案提供了繁體中文的 transformers 模型(包含 ALBERT、BERT、GPT2)及自然語言處理工具(包含斷詞、詞性標記、實體辨識)。
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+ ## Homepage
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+ * https://github.com/ckiplab/ckip-transformers
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  ## Contributers
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  * [Mu Yang](https://muyang.pro) at [CKIP](https://ckip.iis.sinica.edu.tw) (Author & Maintainer)
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+ ## Usage
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+ Please use BertTokenizerFast as tokenizer instead of AutoTokenizer.
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+ 請使用 BertTokenizerFast 而非 AutoTokenizer。
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+ ```
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+ from transformers import (
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+ BertTokenizerFast,
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+ AutoModelForTokenClassification,
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+ )
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+ tokenizer = BertTokenizerFast.from_pretrained('bert-base-chinese')
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+ model = AutoModelForTokenClassification.from_pretrained('ckiplab/albert-base-chinese-ner')
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+ ```
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+ For full usage and more information, please refer to https://github.com/ckiplab/ckip-transformers.
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+ 有關完整使用方法及其他資訊,請參見 https://github.com/ckiplab/ckip-transformers 。