Well i have been playing around a bit with this Jetson Orin Nano a bit and i am frustrated.
Following the information given by the https://www.jetson-ai-lab.com i have not managed much except been able to run ollama, with issues as ollama the newer version started giving responses “GGGGGGGGGGGGGGGGGGGGGGGGGGGG” the whole time. Went looking at a lot of forums and finally rolled back to ver 0.10.0. Ollama is running fine now and it is not my Jetson.
Now i would like to run some more things from the labs and would like to do the stable diffusion. I run all my stuff through docker containers with a docker-compose file . I have extreme difficulty in following the instructions on the labs and when we copy and paste it into cli, i find that they dont work. Is there a better place where we can get better instruction on learning more of our Jetson.
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I understand your frustration with the Jetson Orin Nano and the difficulties you’re facing in following the instructions on the labs. It’s great that you were able to get Ollama running after rolling back to version 0.1.0.
To help you with running Stable Diffusion and other models on your Jetson Orin Nano, I’ll provide some general guidance and recommendations.
Docker Containers and Docker Compose
Using Docker containers and Docker Compose is a great way to manage and run your AI models on the Jetson Orin Nano. This approach allows you to isolate dependencies and ensure reproducibility.
Stable Diffusion
To run Stable Diffusion on your Jetson Orin Nano, you can try the following:
Check the official Stable Diffusion repository on GitHub for Docker container instructions.
Look for a Docker Compose file specifically designed for the Jetson Orin Nano. You can try searching on GitHub or the NVIDIA Jetson forums.
If you can’t find a pre-built Docker Compose file, you can try creating your own using the instructions from the Stable Diffusion repository.
General Tips for Running AI Models on Jetson Orin Nano
Check the documentation: Make sure you’re following the correct instructions for your specific model and Jetson Orin Nano version.
Use the correct Docker image: Ensure you’re using a Docker image that’s compatible with your Jetson Orin Nano and the model you’re trying to run.
Verify dependencies: Double-check that all dependencies are installed and configured correctly.
Monitor resources: Keep an eye on your Jetson Orin Nano’s resources (e.g., memory, CPU, and GPU usage) to ensure you’re not running into bottlenecks.
Join the community: Participate in online forums, such as the NVIDIA Jetson forums or Reddit’s r/Jetson, to connect with other users and get help with specific issues.
Alternative Resources
If you’re finding the instructions on the labs difficult to follow, you can try the following alternative resources:
NVIDIA Jetson Forums: The official NVIDIA Jetson forums are a great place to ask questions and get help from the community.
Reddit’s r/Jetson: This subreddit is dedicated to all things Jetson and has a active community of users and developers.
GitHub: Search for open-source projects and repositories related to the models you’re interested in running on your Jetson Orin Nano.
YouTube: There are many YouTube channels and tutorials dedicated to AI and machine learning on the Jetson Orin Nano.
Comparison with Other Resources
While the labs provide a good starting point, you may find that other resources offer more detailed instructions or better support for your specific use case. Some popular alternatives include:
NVIDIA’s Deep Learning Institute: Offers tutorials, courses, and certifications on deep learning and AI.
JetsonHacks: A community-driven website with tutorials, projects, and resources for the Jetson Orin Nano.
AI Lab: A platform that provides pre-built Docker containers and tutorials for various AI models, including Stable Diffusion.
I hope this helps you get started with running Stable Diffusion and other AI models on your Jetson Orin Nano. If you have any specific questions or need further guidance, feel free to ask!
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@DaneLLL Of everything on the Jetson that was the easiest to do. Even though the new Ollama version 0.11’s are giving errornous responses like GGGGGGGGGGGGGGGGGGGG that i managed to stop by just rolling back to a version 0.10 .
Now i am trying to get a working version of Stable Diffusion working and that is a monumental task as i like to use docker-compose.yaml to run all my containers.
I found one, but now once started it is permission errors inside the container to write files , that i googled and did the chown thing. Rerun and now other issues are popping up. Building my own image is still a bit beyond me as my knowledge of that is a bit slim.
This post is becuase i suck at this and learning from online examples that is not fully functional or wrong architecture is very time consuming. I do enjoy trying to figure out what is wrong by googeling for a fix and then trying it. But heck it looks so easy on the lab pages, you would expect it to work.