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Chinese-Grammatical-error-diagnosis

中文语法纠错研究 基于序列标注的方法

数据集采用的CGED官方提供 转换为序列标注的形式 具体可以看Data中的数据

采用的几个模型如下: HMM\CRF\BILSTM\BERT-CRF\BILSTM-CRF\BERTBILSTMCRF\XLNETBILSTMCRF

以上模型均修改调优自序列标注的代码,并非原创,侵权告诉我删除

前五个模型 环境为python3.7 基于pytorch-gpu 具体怎么合适 根据你的显卡自己配置cuda等等 最后两个模型 环境为pthon3.6 基于tensorflow-gpu

所有程序都在PyCharm上执行,效果一般,xlnet bilstm crf/HMM效果很差,如果你找出原因,麻烦告诉我

部分程序需要,加入parameter,内容在主函数首行

中文语法纠错2020最新研究,我做了一个使用的模型总结,详细可看:https://blog.csdn.net/qq_19889389/article/details/111403458

论文地址(欢迎批评指正):https://iopscience.iop.org/article/10.1088/1742-6596/1948/1/012027/meta

刚学习深度学习,或自学python,在调试程序或者配置环境中难免会遇到一些小问题

Core symbols most depended-on inside this repo

init_weights
called by 58
BERT_CRF/models/transformers/modeling_utils.py
from_pretrained
called by 40
BERT_CRF/models/transformers/modeling_auto.py
load
called by 38
BERT_CRF/models/transformers/modeling_utils.py
prune_linear_layer
called by 21
BERT_CRF/models/transformers/modeling_utils.py
update
called by 20
BERT_CRF/metrics/ner_metrics.py
_tie_or_clone_weights
called by 16
BERT_CRF/models/transformers/modeling_utils.py
print_
called by 15
XLNET_BILSTM_CRF/prepro_utils.py
shape
called by 13
BERT_CRF/models/transformers/modeling_xlm.py

Shape

Method 956
Function 343
Class 276

Languages

Python100%

Modules by API surface

BERT_CRF/models/transformers/modeling_albert.py87 symbols
BERT_CRF/models/transformers/modeling_bert.py78 symbols
BERT_CRF/models/transformers/modeling_albert_bright.py62 symbols
BERT_CRF/models/transformers/tokenization_utils.py50 symbols
BERT_BILSTM_CRF/bert/run_classifier.py49 symbols
BERT_CRF/models/transformers/modeling_xlnet.py45 symbols
BERT_CRF/models/transformers/tokenization_transfo_xl.py38 symbols
BERT_CRF/models/transformers/modeling_distilbert.py38 symbols
BERT_CRF/callback/lr_scheduler.py38 symbols
BERT_CRF/models/transformers/modeling_transfo_xl.py37 symbols
BERT_CRF/models/transformers/modeling_xlm.py36 symbols
BERT_CRF/models/transformers/modeling_utils.py35 symbols

For agents

$ claude mcp add Chinese-Grammatical-error-diagnosis \
  -- python -m otcore.mcp_server <graph>

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