1. 安装好bazel代码构建工具,clone下来tensorflow项目代码,配置好(./configure)
2. clone 本项目地址到tensorflow同级目录,切换到本项目代码目录,运行./configure
3. 编译后台服务

   bazel build //kcws/cc:seg_backend_api

1. 关注待字闺中公众号 回复 kcws 获取语料下载地址: alt text

2. 解压语料到一个目录

3. 切换到代码目录,运行:

pyton kcws/train/process_anno_file <语料目录> chars_for_w2v.txt

使用word2vec 训练 chars_for_w2v (注意-binary 0),得到字嵌入结果vec.txt

bazel build kcws/train:generate_training

./bazel-bin/kcws/train/generate_training vec.txt <语料目录> all.txt

python kcws/train/filter_sentence.py all.txt (得到train.txt , test.txt)

4. 安装好tensorflow,切换到kcws代码目录,运行:

python kcws/train/train_cws_lstm.py --word2vec_path vec.txt --train_data_path <绝对路径到train.txt> --test_data_path test.txt --max_sentence_len 80 --learning_rate 0.001

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