Add refer code to get started

doc/getstarted/concepts/src/infer.py

+import paddle.v2 as paddle
+import numpy as np
+
+paddle.init(use_gpu=False)
+x = paddle.layer.data(name='x', type=paddle.data_type.dense_vector(2))
+y_predict = paddle.layer.fc(input=x, size=1, act=paddle.activation.Linear())
+
+# loading the model which generated by training
+with open('hello_params_pass_90.tar', 'r') as f:
+    parameters = paddle.parameters.Parameters.from_tar(f)
+
+i = [[[1, 2]]]
+
+print paddle.infer(output_layer=y_predict, parameters=parameters, input=i)

doc/getstarted/concepts/src/train.py

@@ -26,6 +26,11 @@ def event_handler(event):
         if event.batch_id % 1 == 0:
             print "Pass %d, Batch %d, Cost %f" % (event.pass_id, event.batch_id,
                                                   event.cost)
+    # product model every 10 pass
+    if isinstance(event, paddle.event.EndPass):
+        if event.pass_id % 10 == 0:
+            with open('params_pass_%d.tar' % event.pass_id, 'w') as f:
+                trainer.save_parameter_to_tar(f)
 
 
 # define training dataset reader

doc/getstarted/concepts/use_concepts_cn.rst

@@ -147,4 +147,9 @@ PaddlePaddle支持不同类型的输入数据，主要包括四种类型，和
 ..  literalinclude:: src/train.py
     :linenos:
 
+使用以上训练好的模型进行预测的例子：
+
+..  literalinclude:: src/infer.py
+    :linenos:
+
 有关线性回归的实际应用，可以参考PaddlePaddle book的 `第一章节 <http://book.paddlepaddle.org/index.html>`_。