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Docs Colab, OBB and typos fixes (#10366)

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Co-authored-by: Olivier Louvignes <olivier@mg-crea.com>
Co-authored-by: RainRat <rainrat78@yahoo.ca>
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Glenn Jocher 2024-04-27 13:16:40 +02:00 • committed by GitHub
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docs/en/guides/nvidia-jetson.md
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@ -54,7 +54,7 @@ The first step after getting your hands on an NVIDIA Jetson device is to flash N
The fastest way to get started with Ultralytics YOLOv8 on NVIDIA Jetson is to run with pre-built docker image for Jetson.
Execute the below command to pull the Docker containter and run on Jetson. This is based on [l4t-pytorch](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch) docker image which contains PyTorch and Torchvision in a Python3 environment.
Execute the below command to pull the Docker container and run on Jetson. This is based on [l4t-pytorch](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch) docker image which contains PyTorch and Torchvision in a Python3 environment.
```sh
t=ultralytics/ultralytics:latest-jetson && sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t