diff --git a/configs/ppyoloe/README.md b/configs/ppyoloe/README.md
index 7a21feeed281987b5726afcc8d958718fd7267c8..aa52b37f049110fe11bb2cf80e31bc19f68c1118 100644
--- a/configs/ppyoloe/README.md
+++ b/configs/ppyoloe/README.md
@@ -99,13 +99,13 @@ python tools/export_model.py -c configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml -o w
 
 ```bash
 # inference single image
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_file=demo/000000014439_640x640.jpg --device=gpu
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_file=demo/000000014439_640x640.jpg --device=gpu
 
 # inference all images in the directory
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_dir=demo/ --device=gpu
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_dir=demo/ --device=gpu
 
 # benchmark
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_file=demo/000000014439_640x640.jpg --device=gpu --run_benchmark=True
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_file=demo/000000014439_640x640.jpg --device=gpu --run_benchmark=True
 ```
 
 If you want to export PP-YOLOE model to **ONNX format**, use following command refer to [PaddleDetection Model Export as ONNX Format Tutorial](../../deploy/EXPORT_ONNX_MODEL_en.md).
diff --git a/configs/ppyoloe/README_cn.md b/configs/ppyoloe/README_cn.md
index ac08a567d721962fcd9e0b0d1dab499f8cf114e6..d770e1cf0407a5b318eec53584e3a6b791a1f42c 100644
--- a/configs/ppyoloe/README_cn.md
+++ b/configs/ppyoloe/README_cn.md
@@ -100,13 +100,13 @@ python tools/export_model.py -c configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml -o w
 
 ```bash
 # 推理单张图片
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_file=demo/000000014439_640x640.jpg --device=gpu
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_file=demo/000000014439_640x640.jpg --device=gpu
 
 # 推理文件夹下的所有图片
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_dir=demo/ --device=gpu
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_dir=demo/ --device=gpu
 
 # benchmark
-CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyolo_r50vd_dcn_1x_coco --image_file=demo/000000014439_640x640.jpg --device=gpu --run_benchmark=True
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_crn_l_300e_coco --image_file=demo/000000014439_640x640.jpg --device=gpu --run_benchmark=True
 ```
 
 如果你想将PP-YOLOE模型导出为**ONNX格式**，参考