diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md
index 749a91b98445d19cc7845b8ad2af4bd5451932af..11837a1b60ec4173549a4d5aed758dde6a6b006f 100644
--- a/configs/ppyolo/README.md
+++ b/configs/ppyolo/README.md
@@ -11,7 +11,7 @@ English | [简体中文](README_cn.md)
 
 ## Introduction
 
-[PP-YOLO](https://arxiv.org/abs/2007.12099) is a optimized model based on YOLOv3 in PaddleDetection，whose performance(mAP on COCO) and inference spped are better than [YOLOv4](https://arxiv.org/abs/2004.10934)，PaddlePaddle 1.8.4(will release in mid-August 202) or [Daily Version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) is required to run this PP-YOLO。
+[PP-YOLO](https://arxiv.org/abs/2007.12099) is a optimized model based on YOLOv3 in PaddleDetection，whose performance(mAP on COCO) and inference spped are better than [YOLOv4](https://arxiv.org/abs/2004.10934)，PaddlePaddle 1.8.4(available on pip now) or [Daily Version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) is required to run this PP-YOLO。
 
 PP-YOLO reached mmAP(IoU=0.5:0.95) as 45.9% on COCO test-dev2017 dataset, and inference speed of FP32 on single V100 is 72.9 FPS, inference speed of FP16 with TensorRT on single V100 is 155.6 FPS.
 
diff --git a/configs/ppyolo/README_cn.md b/configs/ppyolo/README_cn.md
index 1626c582b9ef9a3b580ca191c0386e43e7e29029..4d41cf3467c6ff0be28d2d594b1292b7282e629d 100644
--- a/configs/ppyolo/README_cn.md
+++ b/configs/ppyolo/README_cn.md
@@ -11,7 +11,7 @@
 
 ## 简介
 
-[PP-YOLO](https://arxiv.org/abs/2007.12099)是PaddleDetection优化和改进的YOLOv3的模型，其精度(COCO数据集mAP)和推理速度均优于[YOLOv4](https://arxiv.org/abs/2004.10934)模型，要求使用PaddlePaddle 1.8.4(2020年8月中旬发布)或适当的[develop版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev)。
+[PP-YOLO](https://arxiv.org/abs/2007.12099)是PaddleDetection优化和改进的YOLOv3的模型，其精度(COCO数据集mAP)和推理速度均优于[YOLOv4](https://arxiv.org/abs/2004.10934)模型，要求使用PaddlePaddle 1.8.4(可使用pip安装) 或适当的[develop版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev)。
 
 PP-YOLO在[COCO](http://cocodataset.org) test-dev2017数据集上精度达到45.9%，在单卡V100上FP32推理速度为72.9 FPS, V100上开启TensorRT下FP16推理速度为155.6 FPS。
 
diff --git a/ppdet/modeling/anchor_heads/yolo_head.py b/ppdet/modeling/anchor_heads/yolo_head.py
index ad12a5db3a142871b50bafaf6e8afa1804eeeb54..ade6ca7b58afca61036486e855d452ac997c2837 100644
--- a/ppdet/modeling/anchor_heads/yolo_head.py
+++ b/ppdet/modeling/anchor_heads/yolo_head.py
@@ -77,6 +77,7 @@ class YOLOv3Head(object):
                  downsample=[32, 16, 8],
                  scale_x_y=1.0,
                  clip_bbox=True):
+        check_version("1.8.4")
         self.conv_block_num = conv_block_num
         self.norm_decay = norm_decay
         self.num_classes = num_classes
diff --git a/ppdet/modeling/tests/test_architectures.py b/ppdet/modeling/tests/test_architectures.py
index ab99f30887774fef9792d5c30d35280220ed4ed1..9d6b13a2ada9d0362129cb7a98afc12cb29b6305 100644
--- a/ppdet/modeling/tests/test_architectures.py
+++ b/ppdet/modeling/tests/test_architectures.py
@@ -72,7 +72,7 @@ class TestCascadeRCNN(TestFasterRCNN):
 
 
 @unittest.skipIf(
-    paddle.version.major < "2",
+    paddle.version.full_version < "1.8.4",
     "Paddle 2.0 should be used for YOLOv3 takes scale_x_y as inputs, "
     "disable this unittest for Paddle major version < 2")
 class TestYolov3(TestFasterRCNN):