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417
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1 yr. ago

  • sftpgo

  • It would help to know what model of printer you have and maybe some more photos of different calibration prints. Personally I like this one: https://www.printables.com/model/243257-quick-calicube


    Seems like a temperature issue to me.

    Short parts: Each layer is finished quickly, so the plastic stays warm, and layers fuse strongly before cooling.

    Long parts: Each layer takes much longer to complete, so by the time the nozzle returns, the previous line has already cooled too much, leading to poor interlayer adhesion.

    Try those one by one:

    • Raise nozzle temperature.
    • Raise hotplate temperature.
    • Reduce part cooling fan speed, or disable it after the first few layers.
    • If you have an enclosure, raise the enclosure temperature.

    If it is not temperature related but rather inconsistent extrusion, try:

    • Slow print speed. That makes more consistent extrusion, especially on long straight runs.
    • Increase flow/extrusion multiplier slightly (e.g. +2–4%) to compensate for under-extrusion on long lines.


    This one is off topic, but you mentioned a "debugging" flowchart / q/a for plants or gardening and thats exactly what I am looking for. Do you have a link (or book recommendation) to such a resource?

  • and also only once you've invested the multiple weekends of migrating your whole setup and config to a completely new syntax/concept and invest the necessary time and brainpower to learn everything related.

  • You can use it with non local models.

  • The tool is not just one LLM though. It uses multiple LLMs and multiple other non-llm things.

    Your argument is akin to saying: you can't sit and ride on a wheel, so a wheel can never be used for personal transport. And thus the natural conclusion once you understand what a wheel can do is that you can't sit and ride in a car, so a car is also useless for personal transport.

  • In my experience you can use a LLM to point out typos or grammar errors, but not to actually edit or rephrase your work.

    These will still fall prey to the reason that LLM summaries are bad.

    So you didn't try out this specific LLM based tool, but you extrapolate your experience from generic LLMs to judge it? To me that sounds like a hasty generalization .

    I just want to genuinely now whether this specific tool might be more useful at a specific applications than generic LLMs, yet here on the lemyverse a discussion like that is impossible because AI BAD. It's a sad and frustrating state of affairs.

  • I agree with mostly everything from this blog post. But I am also very curious about projects like these: https://github.com/mindverse/Second-Me that claim to be able to learn to immitate you. Which might end up being good enough for doing the final touches.

    I tried, but it wouldn't run on my hardware. I get to the training process and then it errors out at some point. If anybody has any experience or is willing to try it out, please let us know whether it was actually any good or not.

  • They also forgot Haiku/beos

  • There is a popup?

    I am not sure which of my extensions does it but I have no popup... (and yes I checked in a private window so no cookies)

  • Personally I like it because I tend to not use the github/lab web ui features.

    But one thing that really never clicked with me is the email based issues workflow. I'd prefer to open issues like on github.

  • I'm too lazy to spin up docker containers and config for stuff that would make my life a bit better, but not enough to warrant the hassle... Like for example a finance management software that can hook into my bank. Or document management with automatic email imports etc.

  • LLama 3 8B Instruct: 25tps

    DeepSeek R1 distill qwen 14b: 3.2tps

    To be fair: Motherboard, cpu and ram I bought 6 years ago with an nvidia 1660. Then I bought the Radeon RX 6600 XT on release in 2021, so 4 years ago. But it's a generic gaming rig.

    I would be surprised if 2000$ worth of modern hardware, picked for this specific task would be worse than that mini PC.

  • Well, thats what I said "AI optimized".

    Even my 5 year old 900$ rig can output like 4 tps.

  • Seems pretty decent, but I wonder how it compares to an AI optimized desktop build with the same budget of 2000$.

  • No idea, sorry

    it's a wrapper around dd so that part should work, but probably the menus or some validations don't

  • Since I started using xPipe, everything looks like a nail.

    Not sure if it is part of the free tier, but you can use xPipe to ssh directly into a docker container, on a remote server or on the local machine.