• 2 Posts
  • 143 Comments
Joined 9 months ago
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Cake day: February 14th, 2025

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  • services:
      qbittorrent:
        image: lscr.io/linuxserver/qbittorrent
        container_name: qbittorrent
        environment:
          - PUID=888
          - PGID=888
          - TZ=Australia/Perth
          - WEBUI_PORT=8080
        volumes:
          - ./config:/config
          - /srv/downloads:/downloads
        restart: unless-stopped
        network_mode: "container:wg_out"
    

    this is my compose.yml for a qbittorrent instance.

    the part you’re interested in is the final line. There’s another container with the wireguard instance called “wg_out”. This network mode attaches this qbittorrent container to that wireguard container’s network stack.


  • I’d seen gluetun mentioned but didn’t know what it was for until a moment ago.

    I’ve heard of tailscale and at least know what that does but never used it.

    I personally have a mullvad subscription. I have a container connected to that with wireguard, and then for services I want to use that VPN I just configure them to use the network stack from that container.

    I’m not suggesting that my way is the best but it’s worked well for several years now.



  • Sorry I’m still not really sure what you’re asking for.

    I use Open Web UI, which is the worst name ever, but it’s a web ui for interacting with chat format gen AI models.

    You can install that locally and point it at any of the models hosted remotely by an inference provider.

    So you host the UI but someone else is doing the GPU intensive “inference”.

    There seems to be some models for t his task available on huggingface like this one:

    https://huggingface.co/fakespot-ai/roberta-base-ai-text-detection-v1

    The difficulty may be finding a model which is hosted by an inference provider. Most of the models available on huggingface are just the binary model which you can download and run locally. The popular ones are hosted by inference providers so you can just point a query at their API and get a response.

    As an aside, it’s possible or likely that you know more about how Gen AI works than I do, but I think this type of “probability table for the next token” is from the earlier generations. Or, this type of probability inference might be a foundational concept, but there’s a lot more sophistication layered on top now. I genuinely don’t know. I’m super interested in these technologies but there’s a lot to learn.










  • Honestly, I don’t really have any idea how a laser printer works beyond the basics.

    However, someone has invested the time to create an opensource inkjet printer. It’s a fair assumption that firstly, they know more about printers and hardware than either of us and secondly, they also know everyone prefers laser printers.

    Those two assumptions lead me to the conclusion that there’s a significant barrier to producing an opensource laser printer of which you’re not aware.

    My comment, although unnecessarily douchey, was an allusion to the age old refrain of open source enthusiasts everywhere: if the project isn’t good enough for you, fork it and make your own.






  • Sorry I don’t really understand what your argument actually is.

    Since the dawn of writing, legislators (kings / politicians) have laid down the rules. Regulators (police, tax office) have enforced the rules. And courts decide whether the rules have actually been broken and what the penalties ought to be.

    In the vast majority of self assessment situations, it’s very obvious how the law applies to ones situation, there is very little doubt. You just follow the rules and face penalties for breaches.

    In those few situations which are unclear, you generally have a range of options:

    • review other similar cases heard by courts which might be analogous to your own.
    • consult a specialist who can interpret and apply the rules for you.
    • ask the god damn regulator where you stand and have them help you self-assess.

    Finally, most legislation relating to corporate behavior has safe harbor clauses. That is, where someone has acted reasonably, taken reasonable steps, and made a good-faith attempt to interpret and apply the rules correctly, the regulator won’t penalise them even if they’re found to have breached the rules.

    That is to say penalties are usually only applied where there’s a breach, and there’s no scope to argue that it was a reasonable error.

    This is a fair and transparent structure with which to ensure the rules are applied fairly to everyone. It’s very robust, tolerant of edge cases, and the most efficient compliance structure we have.

    I don’t really know what an alternative would be? If you want a regulator to publish a list of which apps / companies are effected in what way, that’s just nuts. The antithesis of modern democratic economic regulation.