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ultralytics 8.0.151 add DOTAv2.yaml for OBB training (#4258)

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docs/datasets/classify/mnist.md
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@ -45,7 +45,7 @@ To train a CNN model on the MNIST dataset for 100 epochs with an image size of 3
model = YOLO('yolov8n-cls.pt') # load a pretrained model (recommended for training)
# Train the model
model.train(data='mnist', epochs=100, imgsz=32)
results = model.train(data='mnist', epochs=100, imgsz=32)
```
=== "CLI"
@ -69,14 +69,18 @@ If you use the MNIST dataset in your
research or development work, please cite the following paper:
```bibtex
@article{lecun2010mnist,
title={MNIST handwritten digit database},
author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
volume={2},
year={2010}
}
```
!!! note ""
=== "BibTeX"
```bibtex
@article{lecun2010mnist,
title={MNIST handwritten digit database},
author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
volume={2},
year={2010}
}
```
We would like to acknowledge Yann LeCun, Corinna Cortes, and Christopher J.C. Burges for creating and maintaining the MNIST dataset as a valuable resource for the machine learning and computer vision research community. For more information about the MNIST dataset and its creators, visit the [MNIST dataset website](http://yann.lecun.com/exdb/mnist/).