Make YOLO a module (#111)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/yolo/utils/__init__.py

@@ -21,6 +21,32 @@ FONT = 'Arial.ttf'  # https://ultralytics.com/assets/Arial.ttf
 VERBOSE = str(os.getenv('YOLOv5_VERBOSE', True)).lower() == 'true'  # global verbose mode
 TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}'  # tqdm bar format
 LOGGING_NAME = 'yolov5'
+HELP_MSG = \
+    """
+    Please refer to below Usage examples for help running YOLOv8
+    For help visit Ultralytics Community at https://community.ultralytics.com/
+    Submit bug reports to https//github.com/ultralytics/ultralytics
+
+    Install:
+        pip install ultralytics
+
+    Python usage:
+        from ultralytics import YOLO
+
+        model = YOLO.new('yolov8n.yaml')  # create a new model from scratch
+        model = YOLO.load('yolov8n.pt')  # load a pretrained model (recommended for best training results)
+        results = model.train(data='coco128.yaml')
+        results = model.val()
+        results = model.predict(source='bus.jpg')
+        success = model.export(format='onnx')
+
+    CLI usage:
+        yolo task=detect    mode=train     model=yolov8n.yaml ...
+                  classify       predict         yolov8n-cls.yaml
+                  segment        val             yolov8n-seg.yaml
+
+    For all arguments see https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/utils/configs/default.yaml
+    """
 
 # Settings
 # torch.set_printoptions(linewidth=320, precision=5, profile='long')