Fix model in Pose, Segment datasets train FAQ sections (#14877)
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5 changed files with 5 additions and 5 deletions
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@ -133,7 +133,7 @@ Training a YOLOv8 model on the COCO-Pose dataset can be accomplished using eithe
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```bash
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# Start training from a pretrained *.pt model
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yolo detect train data=coco-pose.yaml model=yolov8n.pt epochs=100 imgsz=640
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yolo detect train data=coco-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640
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```
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For more details on the training process and available arguments, check the [training page](../../modes/train.md).
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@ -105,7 +105,7 @@ To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs with an i
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=== "CLI"
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```bash
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yolo detect train data=coco8-pose.yaml model=yolov8n.pt epochs=100 imgsz=640
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yolo detect train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640
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```
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For a comprehensive list of training arguments, refer to the model [Training](../../modes/train.md) page.
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@ -126,7 +126,7 @@ To train a YOLOv8n-pose model on the Tiger-Pose dataset for 100 epochs with an i
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```bash
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# Start training from a pretrained *.pt model
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yolo task=pose mode=train data=tiger-pose.yaml model=yolov8n.pt epochs=100 imgsz=640
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yolo task=pose mode=train data=tiger-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640
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```
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### What configurations does the `tiger-pose.yaml` file include?
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@ -131,7 +131,7 @@ To train a YOLOv8n-seg model on the COCO-Seg dataset for 100 epochs with an imag
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```bash
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# Start training from a pretrained *.pt model
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yolo detect train data=coco-seg.yaml model=yolov8n.pt epochs=100 imgsz=640
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yolo detect train data=coco-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
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```
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### What are the key features of the COCO-Seg dataset?
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@ -106,7 +106,7 @@ To train a **YOLOv8n-seg** model on the COCO8-Seg dataset for 100 epochs with an
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```bash
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# Start training from a pretrained *.pt model
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yolo detect train data=coco8-seg.yaml model=yolov8n.pt epochs=100 imgsz=640
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yolo detect train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
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```
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For a thorough explanation of available arguments and configuration options, you can check the [Training](../../modes/train.md) documentation.
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