This repository provides examples for running AI models and applications on NVIDIA Jetson devices with a single command.
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.
- 🚀 Easy Deployment: Deploy state-of-the-art AI models on Jetson devices in one line.
- 🔄 Versatile Examples: Supports text generation, image generation, vision transformers, computer vision and so on.
- ⚡ Optimized for Jetson: Leverages Nvidia Jetson hardware for efficient performance.
To install the package, run:
pip3 install jetson-examplesNotes:
- Check here for more installation methods
- To upgrade to the latest version, use:
pip3 install jetson-examples --upgrade.
To run and chat with LLaVA, execute:
reComputer run llava
Here are some examples that can be run:
| Example | Type | Model/Data Size | Docker 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 |
| 🆕 yolov8-rail-inspection | Computer Vision | 6M | 13.8GB | reComputer run yolov8-rail-inspection |
Note: You should have enough space to run example, like
LLaVA, at least27.4GBtotally
More Examples can be found examples.md
Want to add your own example? Check out the development guide.
We welcome contributions to improve jetson-examples! If you have an example you'd like to share, please submit a pull request. Thank you to all of our contributors! 🙏
- 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
This project is licensed under the MIT License.