{"id":13858938,"url":"https://github.com/dusty-nv/jetson-containers","last_synced_at":"2025-05-13T22:06:27.455Z","repository":{"id":37391857,"uuid":"260027545","full_name":"dusty-nv/jetson-containers","owner":"dusty-nv","description":"Machine Learning Containers for NVIDIA Jetson and JetPack-L4T","archived":false,"fork":false,"pushed_at":"2025-05-07T14:21:45.000Z","size":228353,"stargazers_count":3026,"open_issues_count":81,"forks_count":592,"subscribers_count":50,"default_branch":"master","last_synced_at":"2025-05-07T15:32:01.788Z","etag":null,"topics":["containers","docker","dockerfiles","jetson","machine-learning","numpy","nvidia","pandas","pytorch","ros-containers","ros2-foxy","scikit-learn","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":["Operation System","Jupyter Notebook","Shell"],"sub_categories":["Embedded Operation System"],"readme":"[![a header for a software project about building containers for AI and machine learning](https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/header_blueprint_rainbow.jpg)](https://www.jetson-ai-lab.com)\n\n# Machine Learning Containers for Jetson and JetPack\n\n[![l4t-pytorch](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/l4t-pytorch_jp51.yml?label=l4t-pytorch)](/packages/l4t/l4t-pytorch)  [![l4t-tensorflow](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/l4t-tensorflow-tf2_jp51.yml?label=l4t-tensorflow)](/packages/l4t/l4t-tensorflow) [![l4t-ml](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/l4t-ml_jp51.yml?label=l4t-ml)](/packages/l4t/l4t-ml) [![l4t-diffusion](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/l4t-diffusion_jp51.yml?label=l4t-diffusion)](/packages/l4t/l4t-diffusion) [![l4t-text-generation](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/l4t-text-generation_jp60.yml?label=l4t-text-generation)](/packages/l4t/l4t-text-generation) ![Jetson PyPI Health](https://img.shields.io/endpoint?url=https://tokk-nv.github.io/jetson-containers/health.json)\n\nModular container build system that provides the latest [**AI/ML packages**](http://jetson.webredirect.org/) for [NVIDIA Jetson](https://developer.nvidia.com/embedded-computing) :rocket::robot:\n\n\u003e [!NOTE]\n\u003e Ubuntu 24.04 containers for JetPack 6 are now available (with CUDA support)\n\u003e\n\u003e \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;`LSB_RELEASE=24.04 jetson-containers build pytorch:2.6`\n\u003e \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;`jetson-containers run dustynv/pytorch:2.6-r36.4.0-cu128-24.04`\n\u003e\n\u003e See the **[`Ubuntu 24.04`](/docs/build.md#2404-containers)** section of the docs for details and a list of available containers 🤗\n\u003e Thanks to all our active contributors from **[`Discord`](https://discord.gg/BmqNSK4886)** for their help with the ongoing builds.\n\n\u003e [!NOTE]\n\u003e SBSA(Arm Server Base System Architecture) is supported for GH200/GB200 and CUDA ARM SBSA Devices.\n\u003e\n\u003e jetson-containers detect automatically the SBSA devices and build the containers for the SBSA devices.\n\u003e \n\u003e Python 3.10 wheels for Ubuntu 22.04 \u0026\u0026 Python 3.12 wheels for Ubuntu 24.04.  \n\u003e wheels: `pip3 install torch torchvision torchaudio --index-url https://pypi.jetson-ai-lab.dev/sbsa/cu128`\n\n| |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |\n|---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| **ML** | [`pytorch`](packages/pytorch) [`tensorflow`](packages/ml/tensorflow) [`jax`](packages/ml/jax) [`onnxruntime`](packages/ml/onnxruntime) [`deepstream`](packages/cv/deepstream) [`holoscan`](packages/cv/holoscan) [`CTranslate2`](packages/ml/ctranslate2) [`JupyterLab`](packages/ml/jupyterlab)                                                                                                                                                                                                                                                                               |\n| **LLM** | [`SGLang`](packages/llm/sglang) [`vLLM`](packages/llm/vllm) [`MLC`](packages/llm/mlc) [`AWQ`](packages/llm/awq) [`transformers`](packages/llm/transformers) [`text-generation-webui`](packages/llm/text-generation-webui) [`ollama`](packages/llm/ollama) [`llama.cpp`](packages/llm/llama_cpp) [`llama-factory`](packages/llm/llama-factory) [`exllama`](packages/llm/exllama) [`AutoGPTQ`](packages/llm/auto_gptq) [`FlashAttention`](packages/attention/flash-attention) [`DeepSpeed`](packages/llm/deepspeed) [`bitsandbytes`](packages/llm/bitsandbytes) [`xformers`](packages/llm/xformers) |\n| **VLM** | [`llava`](packages/vlm/llava) [`llama-vision`](packages/vlm/llama-vision) [`VILA`](packages/vlm/vila) [`LITA`](packages/vlm/lita) [`NanoLLM`](packages/llm/nano_llm) [`ShapeLLM`](packages/vlm/shape-llm) [`Prismatic`](packages/vlm/prismatic) [`xtuner`](packages/vlm/xtuner)                                                                                                                                                                                                                                                                                                                |\n| **VIT** | [`NanoOWL`](packages/vit/nanoowl) [`NanoSAM`](packages/vit/nanosam) [`Segment Anything (SAM)`](packages/vit/sam) [`Track Anything (TAM)`](packages/vit/tam) [`clip_trt`](packages/vit/clip_trt)                                                                                                                                                                                                                                                                                                                                                                                                |\n| **RAG** | [`llama-index`](packages/rag/llama-index) [`langchain`](packages/rag/langchain) [`jetson-copilot`](packages/rag/jetson-copilot) [`NanoDB`](packages/vectordb/nanodb) [`FAISS`](packages/vectordb/faiss) [`RAFT`](packages/ml/rapids/raft)                                                                                                                                                                                                                                                                                                                                                      |\n| **L4T** | [`l4t-pytorch`](packages/ml/l4t/l4t-pytorch) [`l4t-tensorflow`](packages/ml/l4t/l4t-tensorflow) [`l4t-ml`](packages/ml/l4t/l4t-ml) [`l4t-diffusion`](packages/ml/l4t/l4t-diffusion) [`l4t-text-generation`](packages/ml/l4t/l4t-text-generation)                                                                                                                                                                                                                                                                                                                                                              |\n| **CUDA** | [`cupy`](packages/numeric/cupy) [`cuda-python`](packages/cuda/cuda-python) [`pycuda`](packages/cuda/pycuda) [`cv-cuda`](packages/cv/cv-cuda) [`opencv:cuda`](packages/cv/opencv) [`numba`](packages/numeric/numba)                                                                                                                                                                                                                                                                                                                                          |\n| **Robotics** | [`Cosmos`](packages/diffusion/cosmos) [`Genesis`](packages/sim/genesis) [`ROS`](packages/robots/ros) [`LeRobot`](packages/robots/lerobot) [`OpenVLA`](packages/vla/openvla) [`3D Diffusion Policy`](packages/diffusion/3d_diffusion_policy) [`Crossformer`](packages/diffusion/crossformer) [`MimicGen`](packages/sim/mimicgen) [`OpenDroneMap`](packages/robots/opendronemap) [`ZED`](packages/hardware/zed)                                                                                                                                                                                         |\n| **Graphics** | [`stable-diffusion-webui`](packages/diffusion/stable-diffusion-webui) [`comfyui`](packages/diffusion/comfyui) [`nerfstudio`](packages/nerf/nerfstudio) [`meshlab`](packages/nerf/meshlab) [`pixsfm`](packages/nerf/pixsfm) [`gsplat`](packages/nerf/gsplat)                                                                                                                                                                                                                                                                                                                                    |\n| **Mamba** | [`mamba`](packages/mamba/mamba) [`mambavision`](packages/mamba/mambavision) [`cobra`](packages/mamba/cobra) [`dimba`](packages/mamba/dimba) [`videomambasuite`](packages/mamba/videomambasuite)                                                                                                                                                                                                                                                                                                                                                                                                |\n| **Speech** | [`whisper`](packages/speech/whisper) [`whisper_trt`](packages/speech/whisper_trt) [`piper`](packages/speech/piper-tts) [`riva`](packages/speech/riva-client) [`audiocraft`](packages/speech/audiocraft) [`voicecraft`](packages/speech/voicecraft) [`xtts`](packages/speech/xtts)                                                                                                                                                                                                                                                                                                              |\n| **Home/IoT** | [`homeassistant-core`](packages/smart-home/homeassistant-core) [`wyoming-whisper`](packages/smart-home/wyoming/wyoming-whisper) [`wyoming-openwakeword`](packages/smart-home/wyoming/openwakeword) [`wyoming-piper`](packages/smart-home/wyoming/piper)                                                                                                                                                                                                                                                                                                                                        |\n\nSee the [**`packages`**](packages) directory for the full list, including pre-built container images for JetPack/L4T.\n\nUsing 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](/docs/setup.md), and build it on your Jetson:\n\n```bash\n$ jetson-containers build --name=my_container pytorch transformers ros:humble-desktop\n```\n\nThere are shortcuts for running containers too - this will pull or build a [`l4t-pytorch`](packages/l4t/l4t-pytorch) image that's compatible:\n\n```bash\n$ jetson-containers run $(autotag l4t-pytorch)\n```\n\u003e \u003csup\u003e[`jetson-containers run`](/docs/run.md) launches [`docker run`](https://docs.docker.com/engine/reference/commandline/run/) with some added defaults (like `--runtime nvidia`, mounted `/data` cache and devices)\u003c/sup\u003e\u003cbr\u003e\n\u003e \u003csup\u003e[`autotag`](/docs/run.md#autotag) finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.\u003c/sup\u003e\n\nIf you look at any package's readme (like [`l4t-pytorch`](packages/l4t/l4t-pytorch)), it will have detailed instructions for running it.\n\n#### Changing CUDA Versions\n\nYou can rebuild the container stack for different versions of CUDA by setting the `CUDA_VERSION` variable:\n\n```bash\nCUDA_VERSION=12.4 jetson-containers build transformers\n```\n\nIt will then go off and either pull or build all the dependencies needed, including PyTorch and other packages that would be time-consuming to compile.  There is a [Pip server](/docs/build.md#pip-server) that caches the wheels to accelerate builds.  You can also request specific versions of cuDNN, TensorRT, Python, and PyTorch with similar environment variables like [here](/docs/build.md#changing-versions).\n\n## Documentation\n\n\u003ca href=\"https://www.jetson-ai-lab.com\"\u003e\u003cimg align=\"right\" width=\"200\" height=\"200\" src=\"https://nvidia-ai-iot.github.io/jetson-generative-ai-playground/images/JON_Gen-AI-panels.png\"\u003e\u003c/a\u003e\n\n* [Package List](/packages)\n* [Package Definitions](/docs/packages.md)\n* [System Setup](/docs/setup.md)\n* [Building Containers](/docs/build.md)\n* [Running Containers](/docs/run.md)\n\nCheck out the tutorials at the [**Jetson Generative AI Lab**](https://www.jetson-ai-lab.com)!\n\n## Getting Started\n\nRefer to the [System Setup](/docs/setup.md) page for tips about setting up your Docker daemon and memory/storage tuning.\n\n```bash\n# install the container tools\ngit clone https://github.com/dusty-nv/jetson-containers\nbash jetson-containers/install.sh\n\n# automatically pull \u0026 run any container\njetson-containers run $(autotag l4t-pytorch)\n```\n\nOr you can manually run a [container image](https://hub.docker.com/r/dustynv) of your choice without using the helper scripts above:\n\n```bash\nsudo docker run --runtime nvidia -it --rm --network=host dustynv/l4t-pytorch:r36.2.0\n```\n\nLooking for the old jetson-containers?   See the [`legacy`](https://github.com/dusty-nv/jetson-containers/tree/legacy) branch.\n\n## Gallery\n\n\u003ca href=\"https://www.youtube.com/watch?v=UOjqF3YCGkY\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/llamaspeak_llava_clip.gif\"\u003e\u003c/a\u003e\n\u003e [Multimodal Voice Chat with LLaVA-1.5 13B on NVIDIA Jetson AGX Orin](https://www.youtube.com/watch?v=9ObzbbBTbcc) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n\u003cbr/\u003e\n\n\u003ca href=\"https://www.youtube.com/watch?v=hswNSZTvEFE\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/llamaspeak_70b_yt.jpg\" width=\"800px\"\u003e\u003c/a\u003e\n\u003e [Interactive Voice Chat with Llama-2-70B on NVIDIA Jetson AGX Orin](https://www.youtube.com/watch?v=wzLHAgDxMjQ) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n\u003cbr/\u003e\n\n\u003ca href=\"https://www.youtube.com/watch?v=OJT-Ax0CkhU\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/nanodb_tennis.jpg\"\u003e\u003c/a\u003e\n\u003e [Realtime Multimodal VectorDB on NVIDIA Jetson](https://www.youtube.com/watch?v=wzLHAgDxMjQ) (container: [`nanodb`](/packages/vectordb/nanodb))\n\n\u003cbr/\u003e\n\n\u003ca href=\"https://www.jetson-ai-lab.com/tutorial_nanoowl.html\"\u003e\u003cimg src=\"https://github.com/NVIDIA-AI-IOT/nanoowl/raw/main/assets/jetson_person_2x.gif\"\u003e\u003c/a\u003e\n\u003e [NanoOWL - Open Vocabulary Object Detection ViT](https://www.jetson-ai-lab.com/tutorial_nanoowl.html) (container: [`nanoowl`](/packages/vit/nanoowl))\n\n\u003ca href=\"https://www.youtube.com/watch?v=w48i8FmVvLA\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/live_llava.gif\"\u003e\u003c/a\u003e\n\u003e [Live Llava on Jetson AGX Orin](https://youtu.be/X-OXxPiUTuU) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n\u003ca href=\"https://www.youtube.com/watch?v=wZq7ynbgRoE\"\u003e\u003cimg width=\"640px\" src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/live_llava_bear.jpg\"\u003e\u003c/a\u003e\n\u003e [Live Llava 2.0 - VILA + Multimodal NanoDB on Jetson Orin](https://youtu.be/X-OXxPiUTuU) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n\u003ca href=\"https://www.jetson-ai-lab.com/tutorial_slm.html\"\u003e\u003cimg src=\"https://www.jetson-ai-lab.com/images/slm_console.gif\"\u003e\u003c/a\u003e\n\u003e [Small Language Models (SLM) on Jetson Orin Nano](https://www.jetson-ai-lab.com/tutorial_slm.html) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n\u003ca href=\"https://www.jetson-ai-lab.com/tutorial_nano-vlm.html#video-sequences\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/dusty-nv/jetson-containers/docs/docs/images/video_vila_wildfire.gif\"\u003e\u003c/a\u003e\n\u003e [Realtime Video Vision/Language Model with VILA1.5-3b](https://www.jetson-ai-lab.com/tutorial_nano-vlm.html#video-sequences) (container: [`NanoLLM`](https://dusty-nv.github.io/NanoLLM/))\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdusty-nv%2Fjetson-containers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdusty-nv%2Fjetson-containers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdusty-nv%2Fjetson-containers/lists"}