Docs: readme.md contributor image and quick start code fix (#213)

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>

README.md

@@ -86,12 +86,15 @@ YOLOv8 may also be used directly in a Python environment, and accepts the same [
 ```python
 from ultralytics import YOLO
 
-model = YOLO("yolov8n.pt")  # load a pretrained YOLOv8n model
+# Load a model
-
+model = YOLO("yolov8n.yaml")  # build a new model from scratch
-model.train(data="coco128.yaml")  # train the model
+model = YOLO("yolov8n.pt")  # load a pretrained model (recommended for training)
-model.val()  # evaluate model performance on the validation set
+
-model.predict(source="https://ultralytics.com/images/bus.jpg")  # predict on an image
+# Use the model
-model.export(format="onnx")  # export the model to ONNX format
+results = model.train(data="coco128.yaml", epochs=3)  # train the model
+results = model.val()  # evaluate model performance on the validation set
+results = model("https://ultralytics.com/images/bus.jpg")  # predict on an image
+success = YOLO("yolov8n.pt").export(format="onnx")  # export a model to ONNX format
 ```
 
 [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/yolo/v8/models) download automatically from the latest
@@ -204,7 +207,7 @@ We love your input! YOLOv5 and YOLOv8 would not be possible without help from ou
 
 <!-- SVG image from https://opencollective.com/ultralytics/contributors.svg?width=990 -->
 
-<a href="https://github.com/ultralytics/yolov5/graphs/contributors"><img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/image-contributors-1280.png"/></a>
+<a href="https://github.com/ultralytics/ultralytics/graphs/contributors"><img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/image-contributors-1280.png"/></a>
 
 ## <div align="center">License</div>