xcjs

Getting Keycloak and Headscale working together.

But I did it after three weeks.

I captured my efforts in a set of interdependent Ansible roles so I never have to do it again.

The Android version of the app still has the zoom/cursor offset bug when using a software keyboard from when they sunset RDP 8. That has been a severe usability bug for over three years now.

Thank you! I was struggling to remember the proposal name.

Google was working on a feature that would do just that, but I can’t recall the name of it.

They backed down for now due to public outcry, but I expect they’re just biding their time.

Not with this announcement, but it was.

I’m also going to push forward Tilda, which has been my preferred one for a while due to how minimal the UI is.

Yeah - the operating system (or perhaps the display hardware itself, not sure) has to stretch each software pixel to a fractional amount of larger hardware pixels. In the case of upscaling 720p to 1080p, each 720p software pixel has to stretch to 1.33 hardware pixels. This forces blending to occur, which makes the image less sharp.

The worst part of this in my opinion is reading text.

You also lose integer scaling if you need to run a game at common resolutions below 1080p. (720p/800p, etc.)

We all mess up! I hope that helps - let me know if you see improvements!

I think there was a special process to get Nvidia working in WSL. Let me check… (I’m running natively on Linux, so my experience doing it with WSL is limited.)

https://docs.nvidia.com/cuda/wsl-user-guide/index.html - I’m sure you’ve followed this already, but according to this, it looks like you don’t want to install the Nvidia drivers, and only want to install the cuda-toolkit metapackage. I’d follow the instructions from that link closely.

You may also run into performance issues within WSL due to the virtual machine overhead.

Good luck! I’m definitely willing to spend a few minutes offering advice/double checking some configuration settings if things go awry again. Let me know how things go. :-)

It should be split between VRAM and regular RAM, at least if it’s a GGUF model. Maybe it’s not, and that’s what’s wrong?

Ok, so using my “older” 2070 Super, I was able to get a response from a 70B parameter model in 9-12 minutes. (Llama 3 in this case.)

I’m fairly certain that you’re using your CPU or having another issue. Would you like to try and debug your configuration together?

Unfortunately, I don’t expect it to remain free forever.

No offense intended, but are you sure it’s using your GPU? Twenty minutes is about how long my CPU-locked instance takes to run some 70B parameter models.

On my RTX 3060, I generally get responses in seconds.

It’s a W3C managed standard, but there are tons of behavior not spelled out in the specification that platforms can choose to impose.

The standard doesn’t impose a 500 character limit, but there’s nothing that says there can’t be a limit.

Or maybe just let me focus on who I choose to follow? I’m not there for content discovery, though I know that’s why most people are.

I was reflecting on this myself the other day. For all my criticisms of Zuckerberg/Meta (which are very valid), they really didn’t have to release anything concerning LLaMA. They’re practically the only reason we have viable open source weights/models and an engine.

That’s the funny thing about UI/UX - sometimes changing non-functional colors can hurt things.

I mean, sysvinit was just a bunch of root-executed bash scripts. I’m not sure if systemd is really much worse.