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Running Gen AI models and applications on NVIDIA Jetson devices with one-line command

Project description




This repository provides examples for running AI models and applications on NVIDIA Jetson devices. For generative AI, it supports a variety of examples including text generation, image generation, vision transformers, vector databases, and audio models. To run the examples, you need to install the jetson-examples package and use the Seeed Studio reComputer, the edge AI device powered by Jetson Orin. The repo aims to make it easy to deploy state-of-the-art AI models, with just one line of command, on Jetson devices for tasks like language understanding, computer vision, and multimodal processing.

This repo builds upon the work of the Jetson Containers, which provides a modular container build system for various AI/ML packages on NVIDIA Jetson devices. It also leverages resources and tutorials from the Jetson Generative AI Lab, which showcases bringing generative AI to the edge, powered by Jetson hardware.


pip install jetson-examples


To run and chat with LLaVA:

reComputer run llava

Example list

reComputer supports a list of examples from jetson-ai-lab

Here are some examples that can be run:

Example Type Model/Data Size Image Size Command
🆕 llama3 Text (LLM) 4.9GB 10.5GB reComputer run llama3
🆕 ollama Inference Server * 10.5GB reComputer run ollama
LLaVA Text + Vision (VLM) 13GB 14.4GB reComputer run llava
Live LLaVA Text + Vision (VLM) 13GB 20.3GB reComputer run live-llava
stable-diffusion-webui Image Generation 3.97G 7.3GB reComputer run stable-diffusion-webui
nanoowl Vision Transformers(ViT) 613MB 15.1GB reComputer run nanoowl
nanodb Vector Database 76GB 7.0GB reComputer run nanodb
whisper Audio 1.5GB 6.0GB reComputer run whisper

Note: You should have enough space to run example, like LLaVA, at least 27.4GB totally

More Examples can be found

Want to add a Example by yourself? Check this


  • check disk space enough or not before run
  • allow to setting some configs, such as BASE_PATH
  • detect host environment and install what we need
  • support jetson-containers update
  • all type jetson support checking list
  • better table to show example's difference
  • try jetpack 6.0

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