diff --git a/official/cv/googlenet/README.md b/official/cv/googlenet/README.md
index c0a628f306b579bf9139778c3521e6bf558be843..d11fb0fd259551b5f861b415244f527f5072ae76 100644
--- a/official/cv/googlenet/README.md
+++ b/official/cv/googlenet/README.md
@@ -125,7 +125,7 @@ After installing MindSpore via the official website, you can start training and
 
 - running on GPU
 
-  For running on GPU, please change `device_target` from `Ascend` to `GPU` in configuration file src/config.py
+  For running on GPU, please change `device_target` from `Ascend` to `GPU` in configuration file [dataset]_config.yaml
 
   ```python
   # run training example
@@ -145,10 +145,14 @@ After installing MindSpore via the official website, you can start training and
 
   ```python
   # run training example
+  bash run_train_cpu.sh
+  OR
   nohup python train.py --config_path=cifar10_config_cpu.yaml --dataset_name=cifar10 > train.log 2>&1 &
 
   # run evaluation example
-  nohup python eval.py --checkpoint_path=[CHECKPOINT_PATH] > eval.log 2>&1 &  
+  bash run_eval_cpu.sh
+  OR
+  nohup python eval.py --checkpoint_path=[CHECKPOINT_PATH] --config_path=cifar10_config_cpu.yaml > eval.log 2>&1 &
   ```
 
 We use CIFAR-10 dataset by default. Your can also pass `$dataset_type` to the scripts so that select different datasets. For more details, please refer the specify script.
diff --git a/official/cv/googlenet/README_CN.md b/official/cv/googlenet/README_CN.md
index f4aad91b5b13b0e5d8d8b844c70ab0ca3eadbd25..510b1cb07e58c4f42e73c199b95fd922ea83b68e 100644
--- a/official/cv/googlenet/README_CN.md
+++ b/official/cv/googlenet/README_CN.md
@@ -127,7 +127,7 @@ GoogleNet由多个inception模块串联起来，可以更加深入。  降维的
 
 - GPU处理器环境运行
 
-  为了在GPU处理器环境运行，请将配置文件src/config.py中的`device_target`从`Ascend`改为`GPU`
+  为了在GPU处理器环境运行，请将配置文件[dataset]_config.yaml中的`device_target`从`Ascend`改为`GPU`
 
   ```python
   # 运行训练示例
@@ -147,10 +147,14 @@ GoogleNet由多个inception模块串联起来，可以更加深入。  降维的
 
   ```python
   # 运行训练示例
+  bash run_train_cpu.sh
+  OR
   nohup python train.py --config_path=cifar10_config_cpu.yaml --dataset_name=cifar10  > train.log 2>&1 &
 
   # 运行评估示例
-  nohup python eval.py --checkpoint_path=[CHECKPOINT_PATH] > eval.log 2>&1 &
+  bash run_eval_cpu.sh
+  OR
+  nohup python eval.py --checkpoint_path=[CHECKPOINT_PATH] --config_path=cifar10_config_cpu.yaml > eval.log 2>&1 &
   ```
 
 默认使用CIFAR-10数据集。您也可以将`$dataset_type`传入脚本，以便选择其他数据集。如需查看更多详情，请参考指定脚本。
diff --git a/official/cv/googlenet/model_utils/config.py b/official/cv/googlenet/model_utils/config.py
index 2895b1e4a4fa69551be64485d8716b08fa3956a2..b26fa635db174ad1f9c86a8b4c06cc021a2412ea 100644
--- a/official/cv/googlenet/model_utils/config.py
+++ b/official/cv/googlenet/model_utils/config.py
@@ -115,7 +115,7 @@ def get_config():
     """
     parser = argparse.ArgumentParser(description="default name", add_help=False)
     current_dir = os.path.dirname(os.path.abspath(__file__))
-    parser.add_argument("--config_path", type=str, default=os.path.join(current_dir, "../default_config.yaml"),
+    parser.add_argument("--config_path", type=str, default=os.path.join(current_dir, "../cifar10_config.yaml"),
                         help="Config file path")
     path_args, _ = parser.parse_known_args()
     default, helper, choices = parse_yaml(path_args.config_path)