Your ML model cache volume is getting blown up during restart and the model is being re-downloaded during the first search post-restart. Either set it to a path somewhere on your storage, or ensure you’re not blowing up the dynamic volume upon restart.
In my case I changed this:
immich-machine-learning:
...
volumes:
- model-cache:/cache
To that:
immich-machine-learning:
...
volumes:
- ./cache:/cache
I no longer have to wait uncomfortably long when I’m trying to show off Smart Search to a friend, or just need a meme pronto.
That’ll be all.
Is this something that would be recommended if self-hosting off a Synology 920+ NAS?
My NAS does have extra ram to spare because I upgraded it, and has NVME cache 🤗
That’s a Celeron right? I’d try a better AI model. Check this page for the list. You could try the heaviest one. It’ll take a long time to process your library but inference is faster. I don’t know how much faster it is. Maybe it would be fast enough to be usable. If not usable, choose a lighter model. There’s execution times in the table that I assume tell us how heavy the models are. Once you change a model, you have to let it rescan the library.
Yup, the Intel J4125 Celeron 4-Core CPU, 2.0-2.7Ghz.
I switched to the ViT-SO400M-16-SigLIP2-384__webli model, same as what you use. I don’t worry about processing time, but it looks like a more capable model, and I really only use immich for contextual search anyway, so that might be a nice upgrade.
What’s your consideration for choosing this one? I would have thought ViT-B-16-SigLIP2__webli to be slightly more accurate, with faster response and all that while keeping a slightly less RAM consumption (1.4GB less I think).
Seemed to be the most popular. LOL The smart search job hasn’t been running for long, so I’ll check that other one out and see how it compares. If it looks better, I can easily use that.
Did you run the Smart Search job?
Running now.
Let me know how inference goes. I might recommend that to a friend with a similar CPU.