How to reduce the size of best.pt about yolov5

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Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.

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[glenn-jocher]

@suigong1 hey there! 🚀 Reducing the size of your best.pt model file can be approached in a few ways:

1. Model Selection: Opt for a smaller model architecture like YOLOv5s if you haven't already. This has fewer parameters and thus will produce a smaller model file.

   python train.py --data custom.yaml --weights yolov5s.pt

2. Pruning: After training, you can apply model pruning techniques to remove less important weights, which can reduce the model size significantly.

3. Quantization: Implementing quantization can also reduce the model size by decreasing the precision of the weights.

Keep in mind that reducing the model size might affect the accuracy and robustness of your model. If you need more detailed guidance, check out our tips for best training results at https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results/. Good luck! 🍀