CUDA Containers for Edge AI & Robotics

Modular container build system that provides the latest AI/ML packages for NVIDIA Jetson 🚀🤖


ML	`pytorch` `tensorflow` `jax` `onnxruntime` `deepstream` `holoscan` `CTranslate2` `JupyterLab`
LLM	`SGLang` `vLLM` `MLC` `AWQ` `transformers` `text-generation-webui` `text-generation-inference` `ollama` `optimum` `openaigptqmodel` `llama.cpp` `llama-factory` `exllama` `ktransformers` `FlashAttention` `DeepSpeed` `bitsandbytes` `xformers` `xgrammar`
VLM	`llava` `llama-vision` `VILA` `LITA` `NanoLLM` `Prismatic` `xtuner` `gemma_vlm`
VIT	`NanoOWL` `NanoSAM` `Segment Anything (SAM)` `Track Anything (TAM)` `clip_trt`
RAG	`llama-index` `langchain` `jetson-copilot` `NanoDB` `FAISS` `RAFT`
L4T	`l4t-pytorch` `l4t-tensorflow` `l4t-ml` `l4t-diffusion` `l4t-text-generation`
CUDA	`cupy` `cuda-python` `pycuda` `cv-cuda` `opencv:cuda` `numba`
Robotics	`ROS` `LeRobot` `OpenVLA` `3D Diffusion Policy` `Crossformer` `MimicGen` `OpenDroneMap` `ZED` `openpi`
Simulation	`Isaac Sim` `Genesis` `Habitat Sim` `MimicGen` `MuJoCo` `PhysX` `Protomotions` `RoboGen` `RoboMimic` `RoboSuite` `Sapien`
Graphics	`3D Diffusion Policy` `AI Toolkit` `ComfyUI` `Cosmos` `Diffusers` `Diffusion Policy` `FramePack` `Stable Diffusion WebUI` `SD.Next` `nerfstudio` `meshlab` `gsplat`
Mamba	`mamba` `mambavision` `cobra` `dimba` `videomambasuite`
KANs	`pykan` `kat`
xLTSM	`xltsm` `mlstm_kernels`
Speech	`whisper` `whisper_trt` `faster-whisper` `espeak` `whisperx` `Chatterbox TTS` `piper` `riva` `speech-dispatcher` `speaches` `SparkTTS` `riva-client` `audiocraft` `voicecraft` `voice-pro` `xtts`
Home/IoT	`homeassistant-core` `wyoming-whisper` `wyoming-openwakeword` `wyoming-piper`
3DPrintObjects	`PartPacker` `Sparc3D`
Agents	`OpenClaw` `OpenFang` `ZeroClaw`

See the packages directory for the full list, including pre-built container images 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:

$ jetson-containers build --name=my_container pytorch transformers ros:humble-desktop

There are shortcuts for running containers too - this will pull or build a

Thông tin repository

Chủ sở hữudusty-nv

Ngày tạo30/04/2020

Push gần nhất6 ngày trước

Kích thước225.7 MB

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Chủ đềcontainers, docker, dockerfiles, jetson, machine-learning, numpy, nvidia, pandas, pytorch, ros-containers, ros2-foxy, scikit-learn, tensorflow