Update 111-detection-quantization.ipynb

notebooks/111-detection-quantization/111-detection-quantization.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "This tutorial shows how to quantize an object detection model, using OpenVINO's [Post-Training Optimization Tool API](https://docs.openvino.ai/2021.4/pot_compression_api_README.html). \n",
     "\n",
-    "For demonstration purposes, we use a very small dataset of 10 images presenting people at the airport. The images have been resized from the original resolution of 1920x1080 to 960x540. For any real use cases, a representative dataset of about 300 images is recommended. The model used is: [person-detection-retail-0013] (https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/intel/person-detection-retail-0013)"
+    "For demonstration purposes, we use a very small dataset of 10 images presenting people at the airport. The images have been resized from the original resolution of 1920x1080 to 960x540. For any real use cases, a representative dataset of about 300 images is recommended. The model used is: [person-detection-retail-0013](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/intel/person-detection-retail-0013)"
    ]
   },
   {