Add Open Images Dataset V7 pretrained model usage examples (#17090)

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

docs/en/datasets/detect/open-images-v7.md

@@ -29,6 +29,35 @@ keywords: Open Images V7, Google dataset, computer vision, YOLO11 models, object
 | [YOLOv8l](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8l-oiv7.pt) | 640                   | 34.9                 | 596.9                          | 2.43                                | 44.1               | 167.4             |
 | [YOLOv8x](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8x-oiv7.pt) | 640                   | 36.3                 | 860.6                          | 3.56                                | 68.7               | 260.6             |
 
+You can use these pretrained for inference or fine-tuning as follows.
+
+!!! example "Pretrained Model Usage Example"
+
+    === "Python"
+
+        ```python
+        from ultralytics import YOLO
+
+        # Load an Open Images Dataset V7 pretrained YOLOv8n model
+        model = YOLO("yolov8n-oiv7.pt")
+
+        # Run prediction
+        results = model.predict(source="image.jpg")
+
+        # Start training from the pretrained checkpoint
+        results = model.train(data="coco8.yaml", epochs=100, imgsz=640)
+        ```
+
+    === "CLI"
+
+        ```bash
+        # Predict using an Open Images Dataset V7 pretrained model
+        yolo detect predict source=image.jpg model=yolov8n-oiv7.pt
+
+        # Start training from an Open Images Dataset V7 pretrained checkpoint
+        yolo detect train data=coco8.yaml model=yolov8n-oiv7.pt epochs=100 imgsz=640
+        ```
+
 ![Open Images V7 classes visual](https://github.com/ultralytics/docs/releases/download/0/open-images-v7-classes-visual.avif)
 
 ## Key Features