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Update YOLO11 Actions and Docs (#16596)

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10
docs/en/datasets/classify/cifar10.md
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@ -16,7 +16,7 @@ The [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) (Canadian Institute
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Train an <a href="https://www.ultralytics.com/glossary/image-classification">Image Classification</a> Model with CIFAR-10 Dataset using Ultralytics YOLOv8
<strong>Watch:</strong> How to Train an <a href="https://www.ultralytics.com/glossary/image-classification">Image Classification</a> Model with CIFAR-10 Dataset using Ultralytics YOLO11
</p>
## Key Features
@ -50,7 +50,7 @@ To train a YOLO model on the CIFAR-10 dataset for 100 epochs with an image size
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n-cls.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n-cls.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="cifar10", epochs=100, imgsz=32)
@ -60,7 +60,7 @@ To train a YOLO model on the CIFAR-10 dataset for 100 epochs with an image size
```bash
# Start training from a pretrained *.pt model
yolo classify train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32
yolo classify train data=cifar10 model=yolo11n-cls.pt epochs=100 imgsz=32
```
## Sample Images and Annotations
@ -104,7 +104,7 @@ To train a YOLO model on the CIFAR-10 dataset using Ultralytics, you can follow
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n-cls.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n-cls.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="cifar10", epochs=100, imgsz=32)
@ -114,7 +114,7 @@ To train a YOLO model on the CIFAR-10 dataset using Ultralytics, you can follow
```bash
# Start training from a pretrained *.pt model
yolo classify train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32
yolo classify train data=cifar10 model=yolo11n-cls.pt epochs=100 imgsz=32
```
For more details, refer to the model [Training](../../modes/train.md) page.