runtime error

Exit code: 1. Reason: eters, 0 gradients, 8.7 GFLOPs image 1/1 /tmp/gradio/0fad4079240f3f11cde0f23fd5b9ccc7982dd0d746244592d156afd46a9194ef/two.jpeg: 640x640 (no detections), 1571.1ms Speed: 8.5ms preprocess, 1571.1ms inference, 5.3ms postprocess per image at shape (1, 3, 640, 640) Object type: tensor([]) Coordinates: tensor([], size=(0, 4)) Probability: tensor([]) Caching example 3/3 /usr/local/lib/python3.10/site-packages/ultralytics/nn/tasks.py:340: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. return torch.load(file, map_location='cpu'), file # load Ultralytics YOLOv8.0.43 🚀 Python-3.10.14 torch-2.4.1+cu121 CPU YOLOv8n summary (fused): 168 layers, 3151904 parameters, 0 gradients, 8.7 GFLOPs image 1/1 /tmp/gradio/faf866b9235ea8ecd0f1bdd4287bc79303d35e9c9fdb9de8b6cddaff871135fe/three.jpeg: 640x640 (no detections), 2996.8ms Speed: 6.9ms preprocess, 2996.8ms inference, 0.5ms postprocess per image at shape (1, 3, 640, 640) Object type: tensor([]) Coordinates: tensor([], size=(0, 4)) Probability: tensor([]) Traceback (most recent call last): File "/home/user/app/app.py", line 75, in <module> yolo_app.launch(debug=True, enable_queue=True) TypeError: Blocks.launch() got an unexpected keyword argument 'enable_queue'

Container logs: