m_detector.eval()
predictions = m_detector(x)
Mobile-friendly SSDlite variant
x = [torch.rand(3, 320, 320), torch.rand(3, 500, 400)]
m_detector = torchvision.models.detection.ssdlite320_mobilenet_v3_large(pretrained=True)
m_detector.eval()
predictions = m_detector(x)
```
The following accuracies can be obtained on COCO val2017 (full results available in #3403 and #3757):
{:.table.table-striped.table-bordered}
| Model | mAP | mAP@50 | mAP@75 |
| ------------- | ------------- |  ------------- |  ------------- |
| SSD300 VGG16 | 25.1 | 41.5 | 26.2 | 
| SSDlite320 MobileNetV3-Large | 21.3 | 34.3 | 22.1 |
For more details, refer to the documentation.
(Beta) JPEG decoding on the GPU