diff --git a/docs/source/conf.py b/docs/source/conf.py
index ff3639fa..e521b3d6 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -43,6 +43,7 @@ extensions = [
     'sphinx.ext.autodoc',
     'sphinx.ext.viewcode',
     'sphinx.ext.autosummary',
+    'sphinx.ext.mathjax',
 
 ]
 
diff --git a/docs/source/fastNLP.saver.rst b/docs/source/fastNLP.saver.rst
index daa6fbe8..1a02572d 100644
--- a/docs/source/fastNLP.saver.rst
+++ b/docs/source/fastNLP.saver.rst
@@ -1,6 +1,12 @@
 fastNLP.saver 
 ==============
 
+fastNLP.saver.config\_saver 
+----------------------------
+
+.. automodule:: fastNLP.saver.config_saver
+    :members:
+
 fastNLP.saver.logger 
 ---------------------
 
diff --git a/docs/source/figures/procedures.PNG b/docs/source/figures/procedures.PNG
new file mode 100644
index 00000000..982249e8
Binary files /dev/null and b/docs/source/figures/procedures.PNG differ
diff --git a/docs/source/figures/procedures_and_sequence_labeling.png b/docs/source/figures/procedures_and_sequence_labeling.png
deleted file mode 100644
index 06adc051..00000000
Binary files a/docs/source/figures/procedures_and_sequence_labeling.png and /dev/null differ
diff --git a/docs/source/figures/sequence_labeling.PNG b/docs/source/figures/sequence_labeling.PNG
new file mode 100644
index 00000000..397f0a24
Binary files /dev/null and b/docs/source/figures/sequence_labeling.PNG differ
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 37798321..b58f712a 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -12,13 +12,15 @@ fastNLP是一个基于PyTorch的模块化自然语言处理系统，用于快速
 而每个类别包含不同的实现模块。 
 
 大多数当前的NLP模型可以构建在这些模块上，这极大地简化了开发NLP模型的过程。 
-fastNLP的架构如下左图所示：
+fastNLP的架构如图所示：
 
-.. image:: figures/procedures_and_sequence_labeling.png
+.. image:: figures/procedures.PNG
 
-在constructing model部分，以序列标注（上右图）和文本分类（下图）为例进行说明：
+在constructing model部分，以序列标注和文本分类为例进行说明：
 
 .. image:: figures/text_classification.png
+.. image:: figures/sequence_labeling.PNG
+    :width: 400
 
 * encoder module：将输入编码为一些抽象表示，输入的是单词序列，输出向量序列。
 * interaction module：使表示中的信息相互交互，输入的是向量序列，输出的也是向量序列。