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

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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>
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@ -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 = YOLO("yolov8n.pt") # load a pretrained model (recommended for training)
model.train(data="coco128.yaml") # train the model
model.val() # evaluate model performance on the validation set
model.predict(source="https://ultralytics.com/images/bus.jpg") # predict on an image
model.export(format="onnx") # export the model to ONNX format
# Use the model
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>