Improve Docs dataset layout issues (#15696)

Co-authored-by: Francesco Mattioli <Francesco.mttl@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/datasets/segment/crack-seg.md

@@ -135,19 +135,23 @@ Ultralytics YOLO offers advanced real-time object detection, segmentation, and c
 
 If you incorporate the Crack Segmentation Dataset into your research, please use the following BibTeX reference:
 
-```bibtex
-@misc{ crack-bphdr_dataset,
-    title = { crack Dataset },
-    type = { Open Source Dataset },
-    author = { University },
-    howpublished = { \url{ https://universe.roboflow.com/university-bswxt/crack-bphdr } },
-    url = { https://universe.roboflow.com/university-bswxt/crack-bphdr },
-    journal = { Roboflow Universe },
-    publisher = { Roboflow },
-    year = { 2022 },
-    month = { dec },
-    note = { visited on 2024-01-23 },
-}
-```
+!!! Quote ""
+
+    === "BibTeX"
+
+        ```bibtex
+        @misc{ crack-bphdr_dataset,
+            title = { crack Dataset },
+            type = { Open Source Dataset },
+            author = { University },
+            howpublished = { \url{ https://universe.roboflow.com/university-bswxt/crack-bphdr } },
+            url = { https://universe.roboflow.com/university-bswxt/crack-bphdr },
+            journal = { Roboflow Universe },
+            publisher = { Roboflow },
+            year = { 2022 },
+            month = { dec },
+            note = { visited on 2024-01-23 },
+        }
+        ```
 
 This citation format ensures proper accreditation to the creators of the dataset and acknowledges its use in your research.

docs/en/datasets/segment/package-seg.md

@@ -99,24 +99,28 @@ The [Roboflow Package Segmentation Dataset](https://universe.roboflow.com/factor
 
 ### How do I train an Ultralytics YOLOv8 model on the Package Segmentation Dataset?
 
-You can train an Ultralytics YOLOv8n model using both Python and CLI methods. For Python, use the snippet below:
+You can train an Ultralytics YOLOv8n model using both Python and CLI methods. Use the snippets below:
 
-```python
-from ultralytics import YOLO
+!!! Example "Train Example"
 
-# Load a model
-model = YOLO("yolov8n-seg.pt")  # load a pretrained model
+    === "Python"
+    
+        ```python
+        from ultralytics import YOLO
 
-# Train the model
-results = model.train(data="package-seg.yaml", epochs=100, imgsz=640)
-```
+        # Load a model
+        model = YOLO("yolov8n-seg.pt")  # load a pretrained model
 
-For CLI:
+        # Train the model
+        results = model.train(data="package-seg.yaml", epochs=100, imgsz=640)
+        ```
 
-```bash
-# Start training from a pretrained *.pt model
-yolo segment train data=package-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
-```
+    === "CLI"
+        
+        ```bash
+        # Start training from a pretrained *.pt model
+        yolo segment train data=package-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
+        ```
 
 Refer to the model [Training](../../modes/train.md) page for more details.