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README.md
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## All models in this series
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## How to use
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```python
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## Predict info
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## Dataset info
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Data from over
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## Train info
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The training took place over
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## All models in this series
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- [yoloV10n_cs2](https://huggingface.co/Vombit/yolov10n_cs2) (5.5mb)
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- [yoloV10s_cs2](https://huggingface.co/Vombit/yolov10s_cs2) (15.7mb)
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- [yoloV10m_cs2](https://huggingface.co/Vombit/yolov10m_cs2) (31.9mb)
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- [yoloV10b_cs2](https://huggingface.co/Vombit/yolov10b_cs2) (39.7mb)
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- [yoloV10l_cs2](https://huggingface.co/Vombit/yolov10l_cs2) (50.0mb)
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- [yoloV10x_cs2](https://huggingface.co/Vombit/yolov10x_cs2) (61.4mb)
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## How to use
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```python
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## Predict info
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Ultralytics YOLOv8.2.90 🚀 Python-3.12.5 torch-2.3.1+cu121 CUDA:0 (NVIDIA GeForce RTX 4060, 8188MiB)
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- yolov10x_cs2_fp16.engine ()
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- yolov10x_cs2.engine ()
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- yolov10x_cs2_fp16.onnx ()
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- yolov10x_cs2.onnx ()
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- yolov10x_cs2.pt ()
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## Dataset info
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Data from over 120 games, where the footage has been tagged in detail.
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<img width="640" src="https://huggingface.co/Vombit/yolov10x_cs2/resolve/main/labels.jpg">
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<img width="640" src="https://huggingface.co/Vombit/yolov10x_cs2/resolve/main/labels_correlogram.jpg">
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## Train info
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The training took place over 150 epochs.
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<img width="640" src="https://huggingface.co/Vombit/yolov10x_cs2/resolve/main/results.png">
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