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[–] 1 point 4 months ago (2 children)

So.

I did a thing.

I have audiomuse-ai running its main, complete docker compose script, with all containers, on my 8GB Raspi5, and worker-only containers running on:

  • An 8GB bhyve VM on my FreeBSD box
  • An E2-6110 AMD pre-ryzen APU with 16GB of ddr3
  • A Ryzen 5800x w 32GB RAM

They've been running about a week, and I'm a little over a third of the way through

Once the initial analysis is complete, I'll stop all worker containers and leave it all just running fully on the pi5.

I also created a worker-only addon for the 6600T machine, but as it is already running HAOS and Jellyfin, I was getting a lot of OOM-related failures when it was running.

But I also have 32G of used, eBay bought, ddr4 SODIMMs.coming for it.

Bonus: Most of my homelab is in this. The only things missing are my Sophos running OPNsense, and the raspi5. Oh, and my actual desktop machine.

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  • [–] 2 points 4 months ago* (1 child)

    Yo, that’s awesome!

    Pro tip for you, ASR (whisper - lyric detection/transcription) can be kind of bad, but if you have some spare resources, it takes very little to host a local LRCLIB database and clone lrclib.net (they have a GitHub page). This massively speed up lyric analysis for me using the API against a local site instead of getting 429s against lrclib.net or relying on ASR.

    Lyrics are the biggest longest part of the scans. My whole collection was like 3+ weeks with lyrics stuff on, but only 2 days with just MusiCNN and CLAP.

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