Can’t help but think about this old XKCD from 2010.

Products targeted towards businesses have always been unreasonably more expensive than those targeted towards consumers. It sucks for us AI hobbyists that Nvidia are stingy with VRAM on consumer cards, but I don’t find it surprising.

Personally I only have a single RTX 3090, but I know a lot of people online who are stacking multiple consumer cards to run AI. Buying used 3090s and putting them in a mining rig is probably still the best value for money if you need a large amount of VRAM.

How much VRAM do you actually need btw?

Intel NUC running Linux. Not the cheapest solution but can play anything and I have full control over it. At first I tried to find some kind of programmable remote but now we have a wireless keyboard with built-in touchpad.

Biggest downside is that the hardware quality is kind of questionable and the first two broke after 3 years + a few months, so we’re on our third now.

This is my wireguard docker setup:

version: "3.6"
services:
  wireguard:
    image: linuxserver/wireguard
    container_name: wireguard
    cap_add:
      - NET_ADMIN
      - SYS_MODULE
    environment:
      - PUID=116
      - PGID=122
      - TZ=Europe/Stockholm
      - ALLOWEDIPS=192.168.1.0/24
    volumes:
      - /data/torrent/wireguard/config:/config
      - /lib/modules:/lib/modules
    ports:
      - 192.168.1.111:8122:8122  # Deluge webui
      - 192.168.1.111:9127:9127  # jackett webui
      - 192.168.1.111:9666:9666  # prowlarr webui
      - 51820:51820/udp           # wireguard
      - 192.168.1.111:58426:58426  # Deluge RPC
    sysctls:
      - net.ipv4.conf.all.src_valid_mark=1
      - net.ipv6.conf.all.disable_ipv6=1
      - net.ipv6.conf.default.disable_ipv6=1
    restart: unless-stopped

Can reach the webuis from LAN, no other network configuration was necessary. 192.168.1.111 is the server’s LAN address. The other services are configured very similar to your qbittorrent, and don’t expose any ports. Can’t promise it’s 100% correct but it’s working for me.

Add “site:reddit.com” to your google query.

Sad thing is that search engines have got so bad, and usually return so much garbage blog spam that searching directly on reddit is more likely to give useful results. I hope a similar amount of knowledge will build up on Lemmy over time.

Do you mean that you want to build the docker image on one computer, export it to a different computer where it’s going to run, and there shouldn’t be any traces of the build process on the first computer? Perhaps it’s possible with the –output option… Otherwise you could write a small script which combines the commands for docker build, export to file, delete local image, and clean up the system.

https://github.com/miroslavpejic85/mirotalk might be an option. There’s both a server based version and a p2p version IIRC.

I asked someone about this a few days ago, and they claimed to have over 30000 photos in Nextcloud without issues

I suppose “a few” is quite open to interpretation, but I have 50k photos now so if it can handle 100k without getting sluggish it’ll probably be fine for the foreseeable future.

Does Nextcloud handle large numbers of photos nowadays? IIRC when I was comparing programs some years ago I read that both it and Owncloud struggled when you got to a few 10000s of photos.

Ah, nice.

Btw. perhaps you’d like to add:

build: .

to docker-compose.yml so you can just write “docker-compose build” instead of having to do it with a separate docker command. I would submit a PR for it but I have made a bunch of other changes to that file so it’s probably faster if you do it.

Awesome work! Going to try out koboldcpp right away. Currently running llama.cpp in docker on my workstation because it would be such a mess to get cuda toolkit installed natively…

Out of curiosity, isn’t conda a bit redundant in docker since it already is an isolated environment?