Problem using jetson tx2 with jetpack 4.6.3 with ultralytics

My task is to run a docker image where I will work with YOLOv8, I also need to have access to the GPU, which I organized with pytorch. I am running on a jetson tx2 with jetpack version 4.6.3 with python 3.6. To work with YOLO, I need ultralytics, and it requires python 3.7 and higher. Please help me to solve this problem. I took the base image from Nvidia l4t-ml:r32.7.1-py3 with the following packages installed in it: TensorFlow 1.15.5
PyTorch v1.10.0
torchvision v0.11.0
torchaudio v0.10.0
onnx 1.11.0
CuPy 9.2.0
numpy 1.19.5
numba 0.53.1
OpenCV 4.5.0 (with CUDA)
pandas 1.1.5
scipy 1.5.4
scikit-learn 0.24.2
JupyterLab 2.2.9
And I add CUDA settings to it and clone the YOLO repository.

Hi,

We only provide the package for default python version.
So you will need to build PyTorch from the source.

Thanks.