diff --git a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/README.md b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/README.md
index 3b306338b..63a77283e 100644
--- a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/README.md
+++ b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/README.md
@@ -16,7 +16,7 @@ The source code for this sample is available [here](https://github.com/microsoft
 3. Use opencl for IO buffer sample (squeezenet_cpp_app_io.cpp).
 4. Use any sample image as input to the sample.
 5. Download the latest Squeezenet model from the ONNX Model Zoo.
-   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [Squeezenet](https://github.com/onnx/models/tree/master/vision/classification/squeezenet) model from here.
+   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [Squeezenet](https://github.com/onnx/models/tree/master/validated/vision/classification/squeezenet) model from here.
 
 
 ## Install ONNX Runtime for OpenVINO Execution Provider
diff --git a/c_cxx/OpenVINO_EP/Windows/README.md b/c_cxx/OpenVINO_EP/Windows/README.md
index 6dbdb537e..b36e7bb61 100644
--- a/c_cxx/OpenVINO_EP/Windows/README.md
+++ b/c_cxx/OpenVINO_EP/Windows/README.md
@@ -20,7 +20,7 @@
 3. Use opencl for IO buffer sample (squeezenet_cpp_app_io.cpp).
 4. Use any sample image as input to the sample.
 5. Download the latest Squeezenet model from the ONNX Model Zoo.
-   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [Squeezenet](https://github.com/onnx/models/tree/master/vision/classification/squeezenet) model from here.
+   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [Squeezenet](https://github.com/onnx/models/tree/master/validated/vision/classification/squeezenet) model from here.
 
 #### Build ONNX Runtime
 Open x64 Native Tools Command Prompt for VS 2019.
diff --git a/c_sharp/OpenVINO_EP/yolov3_object_detection/README.md b/c_sharp/OpenVINO_EP/yolov3_object_detection/README.md
index fa4142704..4088eb74b 100644
--- a/c_sharp/OpenVINO_EP/yolov3_object_detection/README.md
+++ b/c_sharp/OpenVINO_EP/yolov3_object_detection/README.md
@@ -13,7 +13,7 @@ The source code for this sample is available [here](https://github.com/microsoft
 2. [The Intel<sup>®</sup> Distribution of OpenVINO toolkit](https://docs.openvinotoolkit.org/latest/index.html)
 3. Use any sample Image as input to the sample.
 4. Download the latest YOLOv3 model from the ONNX Model Zoo.
-   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [YOLOv3](https://github.com/onnx/models/tree/master/vision/object_detection_segmentation/yolov3) model from here.
+   This example was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [YOLOv3](https://github.com/onnx/models/tree/master/validated/vision/object_detection_segmentation/yolov3) model from here.
 
 ## Install ONNX Runtime for OpenVINO Execution Provider
 
diff --git a/python/OpenVINO_EP/tiny_yolo_v2_object_detection/README.md b/python/OpenVINO_EP/tiny_yolo_v2_object_detection/README.md
index 037c5d998..7e274b42f 100644
--- a/python/OpenVINO_EP/tiny_yolo_v2_object_detection/README.md
+++ b/python/OpenVINO_EP/tiny_yolo_v2_object_detection/README.md
@@ -10,7 +10,7 @@ The source code for this sample is available [here](https://github.com/microsoft
 
 ## Prerequisites
 1. Download the latest tinyYOLOv2 model from the ONNX Model Zoo.
-   This model was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [tinyYOLOv2](https://github.com/onnx/models/tree/master/vision/object_detection_segmentation/tiny-yolov2) model from here.
+   This model was adapted from [ONNX Model Zoo](https://github.com/onnx/models).Download the latest version of the [tinyYOLOv2](https://github.com/onnx/models/tree/master/validated/vision/object_detection_segmentation/tiny-yolov2) model from here.
 
 ## Install ONNX Runtime for OpenVINO™ Execution Provider
 Please install the onnxruntime-openvino python package from [here](https://pypi.org/project/onnxruntime-openvino). The package for Linux contains prebuilt OpenVINO Libs with ABI 0.
diff --git a/python/OpenVINO_EP/yolov4_object_detection/README.md b/python/OpenVINO_EP/yolov4_object_detection/README.md
index 40c34e078..17c2110e3 100644
--- a/python/OpenVINO_EP/yolov4_object_detection/README.md
+++ b/python/OpenVINO_EP/yolov4_object_detection/README.md
@@ -16,7 +16,7 @@ The source code for this sample is available [here](https://github.com/microsoft
 # How to build
 
 ## Prerequisites
-1. Download the latest version of the [YOLOv4](https://github.com/onnx/models/tree/master/vision/object_detection_segmentation/yolov4) model from here.
+1. Download the latest version of the [YOLOv4](https://github.com/onnx/models/tree/master/validated/vision/object_detection_segmentation/yolov4) model from here.
 
 ## Install ONNX Runtime for OpenVINO™ Execution Provider
 Please install the onnxruntime-openvino python package from [here](https://pypi.org/project/onnxruntime-openvino). The package for Linux contains prebuilt OpenVINO Libs with ABI 0.