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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-08-30 05:52:10 +05:00 • committed by GitHub
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docs/en/integrations/kaggle.md
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@ -22,15 +22,15 @@ Training YOLOv8 models on Kaggle is simple and efficient, thanks to the platform
To get started, access the [Kaggle YOLOv8 Notebook](https://www.kaggle.com/code/ultralytics/yolov8). Kaggle's environment comes with pre-installed libraries like TensorFlow and PyTorch, making the setup process hassle-free.
![What is the kaggle integration with respect to YOLOv8?](https://github.com/user-attachments/assets/4068b343-bb62-462c-9a44-b32413c4a765)
![What is the kaggle integration with respect to YOLOv8?](https://github.com/ultralytics/docs/releases/download/0/kaggle-integration-yolov8.avif)
Once you sign in to your Kaggle account, you can click on the option to copy and edit the code, select a GPU under the accelerator settings, and run the notebook's cells to begin training your model. For a detailed understanding of the model training process and best practices, refer to our [YOLOv8 Model Training guide](../modes/train.md).
![Using kaggle for machine learning model training with a GPU](https://github.com/user-attachments/assets/264f01b9-207b-4a8d-be5d-7b51739e9726)
![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 YOLOv8 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.
![Overview of Options From the Official YOLOv8 Kaggle Notebook Page](https://github.com/user-attachments/assets/bca100a6-fae8-433d-8dfd-1ecf4cc4f691)
![Overview of Options From the Official YOLOv8 Kaggle Notebook Page](https://github.com/ultralytics/docs/releases/download/0/overview-options-yolov8-kaggle-notebook.avif)
These options include: