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Ultralytics Refactor https://ultralytics.com/actions (#17031)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Ultralytics Assistant 2024-10-19 18:20:57 +02:00 • committed by GitHub
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6
docs/en/integrations/kaggle.md
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@ -20,7 +20,7 @@ With more than [10 million users](https://www.kaggle.com/discussions/general/332
Training YOLO11 models on Kaggle is simple and efficient, thanks to the platform's access to powerful GPUs.
To get started, access the [Kaggle YOLO11 Notebook](https://www.kaggle.com/code/ultralytics/yolov8). Kaggle's environment comes with pre-installed libraries like [TensorFlow](https://www.ultralytics.com/glossary/tensorflow) and [PyTorch](https://www.ultralytics.com/glossary/pytorch), making the setup process hassle-free.
To get started, access the [Kaggle YOLO11 Notebook](https://www.kaggle.com/code/glennjocherultralytics/yolo11). Kaggle's environment comes with pre-installed libraries like [TensorFlow](https://www.ultralytics.com/glossary/tensorflow) and [PyTorch](https://www.ultralytics.com/glossary/pytorch), making the setup process hassle-free.
![What is the kaggle integration with respect to YOLO11?](https://github.com/ultralytics/docs/releases/download/0/kaggle-integration-yolov8.avif)
@ -28,7 +28,7 @@ Once you sign in to your Kaggle account, you can click on the option to copy and
![Using kaggle for machine learning model training with a GPU](https://github.com/ultralytics/docs/releases/download/0/using-kaggle-for-machine-learning-model-training-with-a-gpu.avif)
On the [official YOLO11 Kaggle notebook page](https://www.kaggle.com/code/ultralytics/yolov8), if you click on the three dots in the upper right-hand corner, you'll notice more options will pop up.
On the [official YOLO11 Kaggle notebook page](https://www.kaggle.com/code/glennjocherultralytics/yolo11), if you click on the three dots in the upper right-hand corner, you'll notice more options will pop up.
![Overview of Options From the Official YOLO11 Kaggle Notebook Page](https://github.com/ultralytics/docs/releases/download/0/overview-options-yolov8-kaggle-notebook.avif)
@ -95,7 +95,7 @@ Interested in more YOLO11 integrations? Check out the[ Ultralytics integration g
### How do I train a YOLO11 model on Kaggle?
Training a YOLO11 model on Kaggle is straightforward. First, access the [Kaggle YOLO11 Notebook](https://www.kaggle.com/ultralytics/yolov8). Sign in to your Kaggle account, copy and edit the notebook, and select a GPU under the accelerator settings. Run the notebook cells to start training. For more detailed steps, refer to our [YOLO11 Model Training guide](../modes/train.md).
Training a YOLO11 model on Kaggle is straightforward. First, access the [Kaggle YOLO11 Notebook](https://www.kaggle.com/code/glennjocherultralytics/yolo11). Sign in to your Kaggle account, copy and edit the notebook, and select a GPU under the accelerator settings. Run the notebook cells to start training. For more detailed steps, refer to our [YOLO11 Model Training guide](../modes/train.md).
### What are the benefits of using Kaggle for YOLO11 model training?