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tutorial.ipynb

@@ -661,14 +661,14 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "VUOiNLtMP5aG"
+        "id": "ZY2VXXXu74w5"
       },
       "source": [
         "# 3. Train\n",
-        "[<img src=\"https://uploads-ssl.webflow.com/5f6bc60e665f54545a1e52a5/615338ba77195c71bd2c5ab1_computer-vision-flow.png\">](https://roboflow.com/?ref=ultralytics)\n",
-        "*Close the active learning loop by sampling images from your inference conditions with the `roboflow` pip package*\n",
         "\n",
-        "<br>\n",
+        "<p align=\"\"><a href=\"https://roboflow.com/?ref=ultralytics\"><img width=\"1000\" src=\"https://uploads-ssl.webflow.com/5f6bc60e665f54545a1e52a5/615338ba77195c71bd2c5ab1_computer-vision-flow.png\"/></a></p>\n",
+        "Close the active learning loop by sampling images from your inference conditions with the `roboflow` pip package\n",
+        "<br><br>\n",
         "\n",
         "Train a YOLOv5s model on the [COCO128](https://www.kaggle.com/ultralytics/coco128) dataset with `--data coco128.yaml`, starting from pretrained `--weights yolov5s.pt`, or from randomly initialized `--weights '' --cfg yolov5s.yaml`.\n",
         "\n",
@@ -676,7 +676,7 @@
         "automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases)\n",
         "- **[Datasets](https://github.com/ultralytics/yolov5/tree/master/data)** available for autodownload include: [COCO](https://github.com/ultralytics/yolov5/blob/master/data/coco.yaml), [COCO128](https://github.com/ultralytics/yolov5/blob/master/data/coco128.yaml), [VOC](https://github.com/ultralytics/yolov5/blob/master/data/VOC.yaml), [Argoverse](https://github.com/ultralytics/yolov5/blob/master/data/Argoverse.yaml), [VisDrone](https://github.com/ultralytics/yolov5/blob/master/data/VisDrone.yaml), [GlobalWheat](https://github.com/ultralytics/yolov5/blob/master/data/GlobalWheat2020.yaml), [xView](https://github.com/ultralytics/yolov5/blob/master/data/xView.yaml), [Objects365](https://github.com/ultralytics/yolov5/blob/master/data/Objects365.yaml), [SKU-110K](https://github.com/ultralytics/yolov5/blob/master/data/SKU-110K.yaml).\n",
         "- **Training Results** are saved to `runs/train/` with incrementing run directories, i.e. `runs/train/exp2`, `runs/train/exp3` etc.\n",
-        "<br>\n",
+        "<br><br>\n",
         "\n",
         "## Train on Custom Data with Roboflow 🌟 NEW\n",
         "\n",
@@ -684,12 +684,9 @@
         "\n",
         "- Custom Training Example: [https://blog.roboflow.com/how-to-train-yolov5-on-a-custom-dataset/](https://blog.roboflow.com/how-to-train-yolov5-on-a-custom-dataset/?ref=ultralytics)\n",
         "- Custom Training Notebook: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow-ai/yolov5-custom-training-tutorial/blob/main/yolov5-custom-training.ipynb)\n",
-        "\n",
         "<br>\n",
         "\n",
-        "[<img src=\"https://uploads-ssl.webflow.com/5f6bc60e665f54545a1e52a5/6152a275ad4b4ac20cd2e21a_roboflow-annotate.gif\">](https://roboflow.com/?ref=ultralytics)\n",
-        "\n",
-        "*Label images lightning fast (including with model-assisted labeling)*"
+        "<p align=\"\"><a href=\"https://roboflow.com/?ref=ultralytics\"><img width=\"480\" src=\"https://uploads-ssl.webflow.com/5f6bc60e665f54545a1e52a5/6152a275ad4b4ac20cd2e21a_roboflow-annotate.gif\"/></a></p>Label images lightning fast (including with model-assisted labeling)"
       ]
     },
     {