fix broken link (#17130)

example/quantization/README.md

@@ -9,7 +9,7 @@ This folder contains examples of quantizing a FP32 model with Intel® MKL-DNN or
 
 <h2 id="1">Model Quantization with Intel® MKL-DNN</h2>
 
-Intel® MKL-DNN supports quantization with subgraph features on Intel® CPU Platform and can bring performance improvements on the [Intel® Xeon® Scalable Platform](https://www.intel.com/content/www/us/en/processors/xeon/scalable/xeon-scalable-platform.html). A new quantization script `imagenet_gen_qsym_mkldnn.py` has been designed to launch quantization for image-classification models with Intel® MKL-DNN. This script integrates with [Gluon-CV modelzoo](https://gluon-cv.mxnet.io/model_zoo/classification.html), so that more pre-trained models can be downloaded from Gluon-CV and then converted for quantization. To apply quantization flow to your project directly, please refer [Quantize custom models with MKL-DNN backend](https://mxnet.apache.org/tutorials/mkldnn/mkldnn_quantization.html).
+Intel® MKL-DNN supports quantization with subgraph features on Intel® CPU Platform and can bring performance improvements on the [Intel® Xeon® Scalable Platform](https://www.intel.com/content/www/us/en/processors/xeon/scalable/xeon-scalable-platform.html). A new quantization script `imagenet_gen_qsym_mkldnn.py` has been designed to launch quantization for image-classification models with Intel® MKL-DNN. This script integrates with [Gluon-CV modelzoo](https://gluon-cv.mxnet.io/model_zoo/classification.html), so that more pre-trained models can be downloaded from Gluon-CV and then converted for quantization. To apply quantization flow to your project directly, please refer [Quantize custom models with MKL-DNN backend](https://mxnet.apache.org/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_quantization.html).
 
 ```
 usage: imagenet_gen_qsym_mkldnn.py [-h] [--model MODEL] [--epoch EPOCH]