Update to lowercase MkDocs admonitions (#15990)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/tasks/pose.md

@@ -36,7 +36,7 @@ The output of a pose estimation model is a set of points that represent the keyp
   </tr>
 </table>
 
-!!! Tip "Tip"
+!!! tip
 
     YOLOv8 _pose_ models use the `-pose` suffix, i.e. `yolov8n-pose.pt`. These models are trained on the [COCO keypoints](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml) dataset and are suitable for a variety of pose estimation tasks.
 
@@ -82,7 +82,7 @@ YOLOv8 pretrained Pose models are shown here. Detect, Segment and Pose models ar
 
 Train a YOLOv8-pose model on the COCO128-pose dataset.
 
-!!! Example
+!!! example
 
     === "Python"
 
@@ -120,7 +120,7 @@ YOLO pose dataset format can be found in detail in the [Dataset Guide](../datase
 Validate trained YOLOv8n-pose model accuracy on the COCO128-pose dataset. No argument need to passed as the `model`
 retains its training `data` and arguments as model attributes.
 
-!!! Example
+!!! example
 
     === "Python"
 
@@ -150,7 +150,7 @@ retains its training `data` and arguments as model attributes.
 
 Use a trained YOLOv8n-pose model to run predictions on images.
 
-!!! Example
+!!! example
 
     === "Python"
 
@@ -178,7 +178,7 @@ See full `predict` mode details in the [Predict](../modes/predict.md) page.
 
 Export a YOLOv8n Pose model to a different format like ONNX, CoreML, etc.
 
-!!! Example
+!!! example
 
     === "Python"