

Public money, public infra and public funding? :)
Just a stranger trying things.


Public money, public infra and public funding? :)


Google can’t control the device if you’re not running Google. GrapheneOS will still work like before, allowing you to run the apps you want. But the jury is still out on how long… I hope we can have a long term GrapheneOS solution regarding hardware.
I was indeed setting up nvidia and cuda for ML around 2018 and it was not as straight forward or easy as it is today. It was quite annoying and error prone, at least for me who was setting it up on my own for the first time.
Oh I didn’t mean to ask for the link, I just meant to get more information about what you were doing with it, totally understandable! Anyway, cool project!
Oh very interesting! How cool :) Do you then host some kind of website for people to view your animated progress in real time as you run?
Yes!! I wish there were more open source options to interface with fitness trackers and smart watches… I’m upset about all this proprietary crap forcing you to share your data with the manufacturer and depend on their availability and goodwill to access our data… Very frustrating :(


There are great app recommendations here. Perhaps not the habit tracking type, but I love FitoTrack for tracking my runs. No social, no BS, just pure local metrics. Not perfect but entirely usable and serves its purpose.
https://f-droid.org/packages/de.tadris.fitness
Edit: what I love most about all these apps is that they are so lightweight. I have so many apps today which are well above 100MB, sometimes around 500MB and I’m not talking games.
This is so outrageous to me. All of these open source apps by comparison are 10MB or less. Absolutely beautiful.
Remove unused conda packages and caches:
conda clean --all
If you are a Python developer, this can easily be several or tens of GB.


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To run the full 671B sized model (404GB in size), you would need more than 404GB of combined GPU memory and standard memory (and that’s only to run it, you would most probably want it all to be GPU memory to make it run fast).
With 24GB of GPU memory, the largest model which would fit from the R1 series would be the 32b-qwen-distill-q4_K_M (20GB in size) available at ollama (and possibly elsewhere).


Alternatively, you don’t even need podman or any containers, as open-webui can be installed simply using python/conda/pip, if you only care about serving yourself:
https://docs.openwebui.com/getting-started/quick-start/
Much easier to run and maintain IMO. Works wonderfully.
Tried calibre for the first time this week. Geez how simple it was to get it up and place my first eBook on my reader. It was all done in a matter of some few minutes, very intuitively. I didn’t even need to get any documentation open. Great tool!
What are the specs of your setup?
Oh sorry it was not obvious to me that this was a crosspost so I didn’t see the lengthy explanation provided! Indeed, my comment makes little sense, apologies.


This happens to me when using VGA and the connector isn’t well seated. Are you using an analog connector like VGA? Can you double check that the connector is well seated on both ends?


Thanks for sharing your experience. Was XCP-ng considered as a migration target? Would you have some feedback to share on what made it unsuitable for you? Thank you!
They have a special migration tool from VMWare: https://docs.xcp-ng.org/installation/migrate-to-xcp-ng/#-from-vmware


Thank you, I will dig into this to see if there’s something I’m missing, but I did use the same resources the poster did, but the thread may provide more information.


Thanks for the reply! Can you tell me more about what you mean with “check the efi grub install”?
Edit: to be clear, I have a vanilla initramfs booting properly, which is the one automatically built. I’m just trying to replicate it myself.
Vscodium
Free/Libre Open Source Software Binaries of VS Code. VSCodium is a community-driven, freely-licensed binary distribution of Microsoft’s editor VS Code.
https://vscodium.com/