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Update to lowercase MkDocs admonitions (#15990)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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MatthewNoyce 2024-09-06 16:33:26 +01:00 • committed by GitHub
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6
docs/en/modes/benchmark.md
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@ -43,7 +43,7 @@ Once your model is trained and validated, the next logical step is to evaluate i
- **OpenVINO:** For Intel hardware optimization
- **CoreML, TensorFlow SavedModel, and More:** For diverse deployment needs.
!!! Tip "Tip"
!!! tip "Tip"
* Export to ONNX or OpenVINO for up to 3x CPU speedup.
* Export to TensorRT for up to 5x GPU speedup.
@ -52,7 +52,7 @@ Once your model is trained and validated, the next logical step is to evaluate i
Run YOLOv8n benchmarks on all supported export formats including ONNX, TensorRT etc. See Arguments section below for a full list of export arguments.
!!! Example
!!! example
=== "Python"
@ -97,7 +97,7 @@ See full `export` details in the [Export](../modes/export.md) page.
Ultralytics YOLOv8 offers a Benchmark mode to assess your model's performance across different export formats. This mode provides insights into key metrics such as mean Average Precision (mAP50-95), accuracy, and inference time in milliseconds. To run benchmarks, you can use either Python or CLI commands. For example, to benchmark on a GPU:
!!! Example
!!! example
=== "Python"