diff --git a/demo/text-classification/cls_predict.py b/demo/text-classification/predict.py
similarity index 100%
rename from demo/text-classification/cls_predict.py
rename to demo/text-classification/predict.py
diff --git a/demo/text-classification/run_classifier.sh b/demo/text-classification/run_classifier.sh
index e666aac729c4bfa0bb4bd78ba76401faf86871b1..9aaa61a5de0146926c27779c0cece85ab3eab0d3 100644
--- a/demo/text-classification/run_classifier.sh
+++ b/demo/text-classification/run_classifier.sh
@@ -1,7 +1,7 @@
 export CUDA_VISIBLE_DEVICES=5
 
-# User can select senticorp, nlpcc_dbqa, lcqmc for different task
-DATASET="senticorp"
+# User can select chnsenticorp, nlpcc_dbqa, lcqmc for different task
+DATASET="chnsenticorp"
 CKPT_DIR="./ckpt_${DATASET}"
 # Recommending hyper parameters for difference task
 # ChnSentiCorp: batch_size=24, weight_decay=0.01, num_epoch=3, max_seq_len=128, lr=5e-5
diff --git a/demo/text-classification/run_predict.sh b/demo/text-classification/run_predict.sh
index d192c3400c95144248b66250c45a7ddd45b0206f..57b522ab54247dc21711e561b35532229baf17f7 100644
--- a/demo/text-classification/run_predict.sh
+++ b/demo/text-classification/run_predict.sh
@@ -1,4 +1,4 @@
 export CUDA_VISIBLE_DEVICES=5
 
-CKPT_DIR="./ckpt_sentiment_cls/best_model"
-python -u cls_predict.py --checkpoint_dir $CKPT_DIR --max_seq_len 128
+CKPT_DIR="./ckpt_chnsenticorp/best_model"
+python -u predict.py --checkpoint_dir $CKPT_DIR --max_seq_len 128
diff --git a/demo/text-classification/text_classifier.py b/demo/text-classification/text_classifier.py
index c13bfc4eb751be337319ede5682771a80ee04efb..2dd7e8958c46f0e564900b513f9c26c0c7bacf48 100644
--- a/demo/text-classification/text_classifier.py
+++ b/demo/text-classification/text_classifier.py
@@ -43,7 +43,7 @@ if __name__ == '__main__':
 
     # Step2: Download dataset and use ClassifyReader to read dataset
     dataset = None
-    if args.dataset.lower() == "senticorp":
+    if args.dataset.lower() == "chnsenticorp":
         dataset = hub.dataset.ChnSentiCorp()
     elif args.dataset.lower() == "nlpcc_dbqa":
         dataset = hub.dataset.NLPCC_DBQA()