Instructions to use erayyapagci/yolo26n-question-segmentation-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use erayyapagci/yolo26n-question-segmentation-v2 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("erayyapagci/yolo26n-question-segmentation-v2") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Upload model card, weights, and evaluation artifacts
Browse files
README.md
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@@ -38,19 +38,19 @@ Compared with the previously published HF YOLO11M baseline, this release improve
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### Old held-out test set
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| Model | Precision | Recall | mAP50 | mAP50-95 |
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| [YOLO11M Question Segmentation v1](https://huggingface.co/erayyapagci/yolo11m-question-segmentation) | 0.962 | 0.980 | 0.979 | 0.898 |
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| [YOLO26M Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26m-question-segmentation-v2) | 0.990 | 0.982 | 0.988 | 0.920 |
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| [YOLO26N Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26n-question-segmentation-v2) | 0.988 | 0.983 | 0.989 | 0.924 |
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### Combined held-out test set
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| Model | Precision | Recall | mAP50 | mAP50-95 |
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| --- | --- | --- | --- | --- |
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| [YOLO11M Question Segmentation v1](https://huggingface.co/erayyapagci/yolo11m-question-segmentation) | 0.962 | 0.973 | 0.984 | 0.900 |
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| [YOLO26M Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26m-question-segmentation-v2) | 0.987 | 0.978 | 0.992 | 0.957 |
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| [YOLO26N Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26n-question-segmentation-v2) | 0.991 | 0.988 | 0.993 | 0.962 |
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### Benchmark graphs
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### Old held-out test set
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| Model | Size | Precision | Recall | mAP50 | mAP50-95 |
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| --- | --- | --- | --- | --- | --- |
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| [YOLO11M Question Segmentation v1](https://huggingface.co/erayyapagci/yolo11m-question-segmentation) | 116 MB / 20.1M params | 0.962 | 0.980 | 0.979 | 0.898 |
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| [YOLO26M Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26m-question-segmentation-v2) | 168 MB / 21.8M params | 0.990 | 0.982 | 0.988 | 0.920 |
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| [YOLO26N Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26n-question-segmentation-v2) | 5.3 MB / 2.5M params | 0.988 | 0.983 | 0.989 | 0.924 |
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### Combined held-out test set
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| Model | Size | Precision | Recall | mAP50 | mAP50-95 |
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| --- | --- | --- | --- | --- | --- |
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| [YOLO11M Question Segmentation v1](https://huggingface.co/erayyapagci/yolo11m-question-segmentation) | 116 MB / 20.1M params | 0.962 | 0.973 | 0.984 | 0.900 |
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| [YOLO26M Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26m-question-segmentation-v2) | 168 MB / 21.8M params | 0.987 | 0.978 | 0.992 | 0.957 |
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| [YOLO26N Question Segmentation v2](https://huggingface.co/erayyapagci/yolo26n-question-segmentation-v2) | 5.3 MB / 2.5M params | 0.991 | 0.988 | 0.993 | 0.962 |
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### Benchmark graphs
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