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README.md
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license: afl-3.0
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---
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---
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license: afl-3.0
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language:
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- zh
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tags:
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- bert
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- chinesebert
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- MLM
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pipeline_tag: fill-mask
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---
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# ChineseBERT-large
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本项目是将ChineseBERT进行了加工,可供使用者直接使用HuggingFace API进行调用,无需再进行多余的代码配置。
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原论文地址:
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**[ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information](https://arxiv.org/abs/2106.16038)**
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*Zijun Sun, Xiaoya Li, Xiaofei Sun, Yuxian Meng, Xiang Ao, Qing He, Fei Wu and Jiwei Li*
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原项目地址:
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[ChineseBERT github link](https://github.com/ShannonAI/ChineseBert)
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原模型地址:
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[ShannonAI/ChineseBERT-base](https://huggingface.co/ShannonAI/ChineseBERT-base) (该模型无法直接使用HuggingFace API调用)
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# 本项目使用方法
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/iioSnail/ChineseBert/blob/main/demo/ChineseBERT-Demo.ipynb)
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1. 安装pypinyin
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```
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pip install pypinyin
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```
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2. 使用AutoClass加载tokenizer和model
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("iioSnail/ChineseBERT-large", trust_remote_code=True)
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model = AutoModel.from_pretrained("iioSnail/ChineseBERT-large", trust_remote_code=True)
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```
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3. 之后与普通BERT使用方法一致
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```python
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inputs = tokenizer(["我 喜 [MASK] 猫"], return_tensors='pt')
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logits = model(**inputs).logits
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print(tokenizer.decode(logits.argmax(-1)[0, 1:-1]))
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```
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输出:
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```
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tokenizer.decode(logits.argmax(-1)[0, 1:-1])
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```
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# 常见问题
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1. 网络问题,例如:`Connection Error`
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解决方案:将模型下载到本地使用。批量下载方案可参考该[博客](https://blog.csdn.net/zhaohongfei_358/article/details/126222999)
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2. 将模型下载到本地使用时出现报错:`ModuleNotFoundError: No module named 'transformers_modules.iioSnail/ChineseBERT-large'`
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解决方案:将 `iioSnail/ChineseBERT-large` 改为 `iioSnail\ChineseBERT-large`
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