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[DOC]Update documents #53

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20 changes: 11 additions & 9 deletions docs/source/tutorial/zh/index.rst
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入门
=====

.. toctree::
:maxdepth: 1
:titlesonly:

sif
seg
parse
tokenize
vectorization
* `标准项目格式 <sif.rst>`_

* `语法解析 <seg.rst>`_

* `成分分解 <parse.rst>`_

* `令牌化 <tokenize.rst>`_

* `向量化 <vectorization.rst>`_

* `预训练 <pretrain.rst>`_

示例
--------
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14 changes: 1 addition & 13 deletions docs/source/tutorial/zh/pretrain/pub.rst
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* 不使用第三方初始化词表
* 使用第三方初始化词表



模型命名规则：一级版本 + 二级版本 + gensim_luna_stem + 分词规则 + 模型方法 + 维度

Examples：

::

全量版本-全学科的D2V模型路径：
`/share/qlh/d2v_model/luna_pub/luna_pub_all_gensim_luna_stem_general_d2v_256.bin`
（备注：一个D2V模型含4个bin后缀的文件）

模型训练数据说明
##################

* 当前【词向量w2v】【句向量d2v】模型所用的数据均为 【高中学段】 的题目
* 测试数据：`[OpenLUNA.json] <http://base.ustc.edu.cn/data/OpenLUNA/OpenLUNA.json>`_

当前提供以下模型，更多分学科、分题型模型正在训练中，敬请期待
"d2v_all_256"(全科)，"d2v_sci_256"(理科)，"d2v_eng_256"（文科），"d2v_lit_256"(英语)
"d2v_all_256"(全科)，"d2v_sci_256"(理科)，"d2v_eng_256"（英语），"d2v_lit_256"(文科)

模型训练案例
------------
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