diff --git a/tutorial.ipynb b/tutorial.ipynb
index b165062..eaa8865 100644
--- a/tutorial.ipynb
+++ b/tutorial.ipynb
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@@ -564,7 +580,7 @@
         "clear_output()\n",
         "print(f\"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name if torch.cuda.is_available() else 'CPU'})\")"
       ],
-      "execution_count": 1,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -585,7 +601,15 @@
         "\n",
         "`detect.py` runs YOLOv5 inference on a variety of sources, downloading models automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases), and saving results to `runs/detect`. Example inference sources are:\n",
         "\n",
-        "<img align=\"left\" src=\"https://user-images.githubusercontent.com/26833433/114307955-5c7e4e80-9ae2-11eb-9f50-a90e39bee53f.png\" width=\"900\"> "
+        "```shell\n",
+        "python detect.py --source 0  # webcam\n",
+        "                          file.jpg  # image \n",
+        "                          file.mp4  # video\n",
+        "                          path/  # directory\n",
+        "                          path/*.jpg  # glob\n",
+        "                          'https://youtu.be/NUsoVlDFqZg'  # YouTube\n",
+        "                          'rtsp://example.com/media.mp4'  # RTSP, RTMP, HTTP stream\n",
+        "```"
       ]
     },
     {
@@ -601,7 +625,7 @@
         "!python detect.py --weights yolov5s.pt --img 640 --conf 0.25 --source data/images/\n",
         "Image(filename='runs/detect/exp/zidane.jpg', width=600)"
       ],
-      "execution_count": 9,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -675,7 +699,7 @@
         "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco2017val.zip', 'tmp.zip')\n",
         "!unzip -q tmp.zip -d ../datasets && rm tmp.zip"
       ],
-      "execution_count": 10,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -715,7 +739,7 @@
         "# Run YOLOv5x on COCO val2017\n",
         "!python val.py --weights yolov5x.pt --data coco.yaml --img 640 --iou 0.65 --half"
       ],
-      "execution_count": 11,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -839,7 +863,7 @@
         "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip', 'tmp.zip')\n",
         "!unzip -q tmp.zip -d ../ && rm tmp.zip"
       ],
-      "execution_count": 12,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -917,7 +941,7 @@
         "# Train YOLOv5s on COCO128 for 3 epochs\n",
         "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --cache"
       ],
-      "execution_count": 13,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",