Modular container build system that provides various AI/ML packages for NVIDIA Jetson 🚀🤖
See the packages
directory for the full list, including pre-built container images and CI/CD status for JetPack/L4T.
Using the included tools, you can easily combine packages together for building your own containers. Want to run ROS2 with PyTorch and Transformers? No problem - just do the system setup, and build it on your Jetson like this:
$ ./build.sh --name=my_container ros:humble-desktop pytorch transformers
There are shortcuts for running containers too - this will pull or build a l4t-pytorch
image that's compatible:
$ ./run.sh $(./autotag l4t-pytorch)
run.sh
forwards arguments todocker run
with some defaults added (like--runtime nvidia
, mounts a/data
cache, and detects devices)
autotag
finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.
If you look at any package's readme (like l4t-pytorch
), it will have detailed instructions for running it's container.
Looking for the old jetson-containers? See the legacy
branch
Refer to the System Setup page for tips about setting up your Docker daemon and memory/storage tuning.
sudo apt-get update && sudo apt-get install git python3-pip
git clone https://github.com/dusty-nv/jetson-containers
cd jetson-containers
pip3 install -r requirements.txt
./run.sh $(./autotag l4t-pytorch)
Check out the tutorials on the Jetson Generative AI Playground!