Reformat Markdown code blocks (#12795)

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

docs/en/datasets/pose/coco.md

@@ -61,10 +61,10 @@ To train a YOLOv8n-pose model on the COCO-Pose dataset for 100 epochs with an im
         from ultralytics import YOLO
 
         # Load a model
-        model = YOLO('yolov8n-pose.pt')  # load a pretrained model (recommended for training)
+        model = YOLO("yolov8n-pose.pt")  # load a pretrained model (recommended for training)
 
         # Train the model
-        results = model.train(data='coco-pose.yaml', epochs=100, imgsz=640)
+        results = model.train(data="coco-pose.yaml", epochs=100, imgsz=640)
         ```
 
     === "CLI"

docs/en/datasets/pose/coco8-pose.md

@@ -34,10 +34,10 @@ To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs with an i
         from ultralytics import YOLO
 
         # Load a model
-        model = YOLO('yolov8n-pose.pt')  # load a pretrained model (recommended for training)
+        model = YOLO("yolov8n-pose.pt")  # load a pretrained model (recommended for training)
 
         # Train the model
-        results = model.train(data='coco8-pose.yaml', epochs=100, imgsz=640)
+        results = model.train(data="coco8-pose.yaml", epochs=100, imgsz=640)
         ```
 
     === "CLI"

docs/en/datasets/pose/index.md

@@ -72,10 +72,10 @@ The `train` and `val` fields specify the paths to the directories containing the
         from ultralytics import YOLO
 
         # Load a model
-        model = YOLO('yolov8n-pose.pt')  # load a pretrained model (recommended for training)
+        model = YOLO("yolov8n-pose.pt")  # load a pretrained model (recommended for training)
 
         # Train the model
-        results = model.train(data='coco8-pose.yaml', epochs=100, imgsz=640)
+        results = model.train(data="coco8-pose.yaml", epochs=100, imgsz=640)
         ```
     === "CLI"
 
@@ -132,7 +132,7 @@ Ultralytics provides a convenient conversion tool to convert labels from the pop
         ```python
         from ultralytics.data.converter import convert_coco
 
-        convert_coco(labels_dir='path/to/coco/annotations/', use_keypoints=True)
+        convert_coco(labels_dir="path/to/coco/annotations/", use_keypoints=True)
         ```
 
 This conversion tool can be used to convert the COCO dataset or any dataset in the COCO format to the Ultralytics YOLO format. The `use_keypoints` parameter specifies whether to include keypoints (for pose estimation) in the converted labels.

docs/en/datasets/pose/tiger-pose.md

@@ -47,10 +47,10 @@ To train a YOLOv8n-pose model on the Tiger-Pose dataset for 100 epochs with an i
         from ultralytics import YOLO
 
         # Load a model
-        model = YOLO('yolov8n-pose.pt')  # load a pretrained model (recommended for training)
+        model = YOLO("yolov8n-pose.pt")  # load a pretrained model (recommended for training)
 
         # Train the model
-        results = model.train(data='tiger-pose.yaml', epochs=100, imgsz=640)
+        results = model.train(data="tiger-pose.yaml", epochs=100, imgsz=640)
         ```
 
     === "CLI"