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README.md

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@@ -299,9 +299,9 @@ CUDA_VISIBLE_DEVICES=0 python train/train_wc.py --input_file=/data/EssayKiller/
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| 模型 | 参数量 | 下载链接 | 备注 |
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| ------------- |:-------------:|:----:|:---:|
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| EAST | < 0.1 Billion | [GoogleDrive](https://pan.baidu.com/s/1S9WpyXZ_wVWbKo-WsB0q5A) 提取码:sxhh| 检测模型 |
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| EAST | < 0.1 Billion | [GoogleDrive](https://drive.google.com/file/d/1fF4IYaL7CWghYCDvRrACM57WVx83Yvny/view?usp=sharing) | 检测模型 |
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| CRNN | < 0.1 Billion | [网盘链接](https://eyun.baidu.com/s/3dEUJJg9) 提取码:vKeD| 识别模型 |
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| BERT | 0.1 Billion | [GoogleDrive](https://pan.baidu.com/s/1BrdFSx9_n1q2uWBiQrpalw) 提取码:kim2| 摘要模型 |
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| BERT | 0.1 Billion | [GoogleDrive](https://drive.google.com/file/d/15DbA07DZNT3gMXu2aLliA3CkuR5XHhlt/view?usp=sharing) | 摘要模型 |
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| GPT-2 | 1.5 Billion | [GoogleDrive](https://drive.google.com/file/d/1ujWYTOvRLGJX0raH-f-lPZa3-RN58ZQx/view?usp=sharing) | 生成模型 |
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整个AI的参数量分布不均匀,主要原因在于,这是一个语言类AI,99%的参数量集中在语言网络中,其中GPT-2(15亿)占88%,BERT(1.1亿)占7%,其他的识别网络和判分网络共占5%。

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