📝 Writing docs.

docs/md/home.md

@@ -58,6 +58,8 @@ pip install tensorflow
 pip install tensorflow-gpu
 ```
 
+**You could work with tensorflow==1.13.0 for embedding and labeling tasks, but some customized classification models might crash**
+
 ### Example Usage
 
 lets run a NER labeling model with BLSTM Model.

docs/md/text_classification_model.md

@@ -41,6 +41,9 @@ Then train our first model. All models provided some APIs, so you could use any
 import kashgari
 from kashgari.tasks.classification import BiLSTM_Model
 
+import logging
+logging.basicConfig(level='DEBUG')
+
 model = BiLSTM_Model()
 model.fit(train_x, train_y, valid_x, valid_y)
 
@@ -134,6 +137,9 @@ from tensorflow import keras
 from kashgari.tasks.classification.base_model import BaseClassificationModel
 from kashgari.layers import L
 
+import logging
+logging.basicConfig(level='DEBUG')
+
 
 class DoubleBLSTMModel(BaseClassificationModel):
     """Bidirectional LSTM Sequence Labeling Model"""

docs/md/text_labeling_model.md

@@ -147,6 +147,8 @@ from tensorflow import keras
 from kashgari.tasks.labeling.base_model import BaseLabelingModel
 from kashgari.layers import L
 
+import logging
+logging.basicConfig(level='DEBUG')
 
 class DoubleBLSTMModel(BaseLabelingModel):
     """Bidirectional LSTM Sequence Labeling Model"""