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Docs Prettier reformat (#13483)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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docs/en/tasks/classify.md
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@ -34,7 +34,7 @@ YOLOv8 pretrained Classify models are shown here. Detect, Segment and Pose model
[Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) on first use.
| Model | size<br><sup>(pixels) | acc<br><sup>top1 | acc<br><sup>top5 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) at 640 |
|----------------------------------------------------------------------------------------------|-----------------------|------------------|------------------|--------------------------------|-------------------------------------|--------------------|--------------------------|
| -------------------------------------------------------------------------------------------- | --------------------- | ---------------- | ---------------- | ------------------------------ | ----------------------------------- | ------------------ | ------------------------ |
| [YOLOv8n-cls](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n-cls.pt) | 224 | 69.0 | 88.3 | 12.9 | 0.31 | 2.7 | 4.3 |
| [YOLOv8s-cls](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8s-cls.pt) | 224 | 73.8 | 91.7 | 23.4 | 0.35 | 6.4 | 13.5 |
| [YOLOv8m-cls](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8m-cls.pt) | 224 | 76.8 | 93.5 | 85.4 | 0.62 | 17.0 | 42.7 |
@ -163,19 +163,19 @@ Export a YOLOv8n-cls model to a different format like ONNX, CoreML, etc.
Available YOLOv8-cls export formats are in the table below. You can export to any format using the `format` argument, i.e. `format='onnx'` or `format='engine'`. You can predict or validate directly on exported models, i.e. `yolo predict model=yolov8n-cls.onnx`. Usage examples are shown for your model after export completes.
| Format | `format` Argument | Model | Metadata | Arguments |
|---------------------------------------------------|-------------------|-------------------------------|----------|----------------------------------------------------------------------|
| [PyTorch](https://pytorch.org/) | - | `yolov8n-cls.pt` | ✅ | - |
| [TorchScript](../integrations/torchscript.md) | `torchscript` | `yolov8n-cls.torchscript` | ✅ | `imgsz`, `optimize`, `batch` |
| [ONNX](../integrations/onnx.md) | `onnx` | `yolov8n-cls.onnx` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `opset`, `batch` |
| [OpenVINO](../integrations/openvino.md) | `openvino` | `yolov8n-cls_openvino_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TensorRT](../integrations/tensorrt.md) | `engine` | `yolov8n-cls.engine` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `workspace`, `int8`, `batch` |
| [CoreML](../integrations/coreml.md) | `coreml` | `yolov8n-cls.mlpackage` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-cls_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-cls.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-cls.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-cls_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-cls_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-cls_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-cls_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |
| ------------------------------------------------- | ----------------- | ----------------------------- | -------- | -------------------------------------------------------------------- |
| [PyTorch](https://pytorch.org/) | - | `yolov8n-cls.pt` | ✅ | - |
| [TorchScript](../integrations/torchscript.md) | `torchscript` | `yolov8n-cls.torchscript` | ✅ | `imgsz`, `optimize`, `batch` |
| [ONNX](../integrations/onnx.md) | `onnx` | `yolov8n-cls.onnx` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `opset`, `batch` |
| [OpenVINO](../integrations/openvino.md) | `openvino` | `yolov8n-cls_openvino_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TensorRT](../integrations/tensorrt.md) | `engine` | `yolov8n-cls.engine` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `workspace`, `int8`, `batch` |
| [CoreML](../integrations/coreml.md) | `coreml` | `yolov8n-cls.mlpackage` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-cls_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-cls.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-cls.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-cls_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-cls_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-cls_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-cls_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |
See full `export` details in the [Export](../modes/export.md) page.