-
Notifications
You must be signed in to change notification settings - Fork 648
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
能不能提供一个通用Python训练代码啊 #115
Comments
我这边最近在使用,所以把训练和使用模型封装了下: |
Alley <[email protected]>于2018年5月16日 周三10:13写道:
我这边最近在使用,所以把训练和使用模型封装了下:
https://github.com/AlleyEli/kcws 你可以看readme最上面加的部分,进行操作!
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
<#115 (comment)>, or mute
the thread
<https://github.com/notifications/unsubscribe-auth/ADxsF9nsGVobAWgoskSTmlWks23aCoylks5ty4tMgaJpZM4TEtOC>
.
好的,多谢啦
--
|
@forever1dream 不好意思,才发现两边同一个人 嘿嘿! 有缘 |
@AlleyEli 哈哈 我不怎么会Python |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
train_cws.py 训练 输入特征:字的 word2vec向量表示
train_pos.py 训练 输入特征是:词的 word2vec向量表示,文档写的最大50个词,向量的1-50是词的word2vec表示,不够的用0填充;字的word2vec向量表示,每个词最大5个词,超过5个字的用最后一个字代替第五个字,就是一个50X5的向量;词性标注结果个词的向量长度一致50,所以训练语料是长度为350的向量,1-50是词,51-300是字,301-350是预测结果。
想写一个train NE 的代码模仿train_pos.py: 1-50词,51-300字,301-350词性,NE表示和字序列类似每个最大长度15,就是15X50,351-1100是预测结果,但是改代码失败了
能不能一个train.py, 准备好训练语料之后,自定义特征以及对应的特征长度,还有定义输出
对Python不熟悉,想用这个训练model之后C++直接调用,求大神指教。
The text was updated successfully, but these errors were encountered: