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@baobaoboa hello there! 👋 The terms
You can consider using these techniques when you need to deploy your model to environments with limited resources or when you require faster inference times. Fine-tuning (re-training) a model after applying these techniques is indeed possible and sometimes necessary to regain lost accuracy due to the optimization process. It allows the model to adjust to the changes and potentially recover performance. For more details on how to apply these techniques with YOLOv8, you can refer to our documentation at https://docs.ultralytics.com. Happy optimizing! 😊 |
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What's the difference between
export half
,pruning
, andsparsing
? When should I consider using one of them?If I consider using them, would it be fine to try to fine-tune it again (re-train the model)?
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