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Add Tips for Model Training Docs Page (#14011)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Abirami Vina 2024-06-26 20:04:11 +05:30 • committed by GitHub
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docs/en/models/yolov10.md
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@ -137,7 +137,7 @@ For predicting new images with YOLOv10:
# Display the results
results[0].show()
```
```
=== "CLI"
@ -161,7 +161,7 @@ For training YOLOv10 on a custom dataset:
# Train the model
model.train(data="coco8.yaml", epochs=100, imgsz=640)
```
=== "CLI"
```bash
@ -171,15 +171,15 @@ For training YOLOv10 on a custom dataset:
# Build a YOLOv10n model from scratch and run inference on the 'bus.jpg' image
yolo predict model=yolov10n.yaml source=path/to/bus.jpg
```
## Supported Tasks and Modes
The YOLOv10 models series offers a range of models, each optimized for high-performance [Object Detection](../tasks/detect.md). These models cater to varying computational needs and accuracy requirements, making them versatile for a wide array of applications.
| Model | Filenames | Tasks | Inference | Validation | Training | Export |
|---------|------------------------------------------------------------------------|----------------------------------------------|-----------|------------|----------|--------|
| YOLOv10 | `yolov10n.pt` `yolov10s.pt` `yolov10m.pt` `yolov10l.pt` `yolov10x.pt` | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
| Model | Filenames | Tasks | Inference | Validation | Training | Export |
| ------- | --------------------------------------------------------------------- | -------------------------------------- | --------- | ---------- | -------- | ------ |
| YOLOv10 | `yolov10n.pt` `yolov10s.pt` `yolov10m.pt` `yolov10l.pt` `yolov10x.pt` | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
## Exporting YOLOv10