diff --git a/cv/detection/yolov8/paddlepaddle/README.md b/cv/detection/yolov8/paddlepaddle/README.md
new file mode 100755
index 0000000000000000000000000000000000000000..5ca2c42a37977ebd2b7ca758a02f6f31ea95e528
--- /dev/null
+++ b/cv/detection/yolov8/paddlepaddle/README.md
@@ -0,0 +1,39 @@
+# YOLOv8
+
+## Model description
+
+YOLOv8 is the world's most loved vision AI, representing <a href="https://ultralytics.com">Ultralytics</a> open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.
+
+## Step 1: Installation
+
+```bash
+cd deepsparkhub/cv/detection/yolov8/paddlepaddle/
+git clone -b release/2.7 https://github.com/PaddlePaddle/PaddleYOLO.git
+cd PaddleYOLO/
+pip3 install -r requirements.txt
+python3 setup.py install
+```
+
+## Step 2: Preparing datasets
+
+```bash
+python3 dataset/coco/download_coco.py
+```
+
+## Step 3: Training
+
+```bash
+# Make sure your dataset path is the same as above
+export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+# Select $config_yaml from "configs/yolov5" as you wish
+config_yaml=configs/yolov8/yolov8_s_500e_coco.yml
+python3 -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c ${config_yaml} --amp --eval
+```
+
+## Results
+GPUs|Model|FPS|ACC
+----|---|---|---
+BI-V100 x8|YOLOv8-s| 20.0911 images/s | bbox ap: 0.259
+
+## Reference
+- [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)