Pumpkin Escobar

Yeah yeah yeah… yeah

no fact checking and a ton of bots being added? Sounds like a fantastic place to spend time. /s

I haven’t seen Cunk on Life yet but Cunk on Britain and Cunk on Earth are great if you like a sort of dry/stupid humor. Try 2-5 minutes of it, if you like it even a little I bet you’ll like it a lot by the end.

Seriously, I’d love to see this chart, earnings chart and PE ratio chart to really see the whole picture

Yeah, I phrased that poorly, I was painfully aware of the Haitians eating cats BS, I meant this more like “why wait until the last paragraph to drop that key bit of information?” Clumsy writing / story structure at the very least.

Why is the fact that she’s a us citizen in the last paragraph?

EDIT: I phrased this poorly, I meant, why hold that information back until the last paragraph? That’s sort of the key part of the story.

Ollama and openwebui for a nice web interface.

Besides the user engagement reasons, it’s pretty obvious why Elon Musk specifically would want people to not check sources. Nothing better for Xitter disinformation campaigns than not having readily available links to other sources.

What a Xithole.

DNFTA

But, I thought Trump was all about state’s rights? This is very confusing. /s

Similar to previous reply about MATE with font size changes, I do that with plasma. I hadn’t seen plasma big screen you linked, I’ll definitely try that one out. I’ve wondered about https://en.m.wikipedia.org/wiki/Plasma_Mobile? Like these sort of niche projects don’t always get a lot of attention, if the bigscreen project doesn’t work out, I’d bet the plasma mobile project is fairly active and given the way it scales for displays might work really well on a tv

Speaking of scaling since you mentioned it. I have noticed scaling in general feels a lot better in Wayland. If you’d only tried it in X11 before, might want to see if Wayland works better for you.

First a caveat/warning - you’ll need a beefy GPU to run larger models, there are some smaller models that perform pretty well.

Adding a medium amount of extra information for you or anyone else that might want to get into running models locally

Tools

• Ollama - great app for downloading/managing/running models locally
• OpenWebUI - A web app that provides a UI like the ChatGPT web app, but can use local models
• continue.dev - A VS Code extension that can use ollama to give a github copilot-like AI assistant running against a local model (can also connect to Anthropic Claude, etc…)

Models

If you look at https://ollama.com/library?sort=featured you can see models

Model size is measured by parameter count. Generally higher parameter models are better (more “smart”, more accurate) but it’s very challenging/slow to run anything over 25b parameters on consumer GPUs. I tend to find 8-13b parameter models are a sort of sweet spot, the 1-4b parameter models are meant more for really low power devices, they’ll give you OK results for simple requests and summarizing, but they’re not going to wow you.

If you look at the ‘tags’ for the models listed below, you’ll see things like 8b-instruct-q8_0 or 8b-instruct-q4_0. The q part refers to quantization, or shrinking/compressing a model and the number after that is roughly how aggressively it was compressed. Note the size of each tag and how the size reduces as the quantization gets more aggressive (smaller numbers). You can roughly think of this size number as “how much video ram do I need to run this model”. For me, I try to aim for q8 models, fp16 if they can run in my GPU. I wouldn’t try to use anything below q4 quantization, there seems to be a lot of quality loss below q4. Models can run partially or even fully on a CPU but that’s much slower. Ollama doesn’t yet support these new NPUs found in new laptops/processors, but work is happening there.

• Llama 3.1 - The 8b instruct model is pretty good, decent speed and good quality. This is a good “default” model to use
• Llama 3.2 - This model was just released yesterday. I’m only seeing the 1b and 3b models right now. They’ve changed the 8b model to 11b, I’m assuming the 11b model is going to be my new goto when it’s available.
• Deepseek Coder v2 - A great coding assistant model
• Command-r - This is a more niche model, mainly useful for RAG. It’s only available in a 35b parameter model, so not all that feasible to run locally
• Mistral small - A really good model, in the ballpark of Llama. I haven’t had quite as much luck with this as with Llama but it is good and I just saw that a new version was released 8 days ago, will need to check it out again

It’s a good thing that real open source models are getting good enough to compete with or exceed OpenAI.

surely he’ll be less of a twat then. right?

I guess it wasn’t bacon I hate for breakfast yesterday.

Why do you hate bacon, are you a windmill?

Lan-mouse looks great but keep in mind that there’s no network encryption right now. There is a GitHub ticket open and the developer seems eager to add encryption. It’s just worth understanding that all your keystrokes are going across the network unencrypted.

Things I will bet money on

• They will produce no evidence of any wrongdoing uncovered from any of these raids
• They will give some cryptic statement that tries to make it sound like they did find something
• Texas lawmakers will continue to not hold Paxton accountable for anything

More than distro hopping maybe try out a zen kernel or compiling kernel yourself and changing kernel config and scheduler, or a newer version of the stock kernel?

I’m not super current on what’s in each kernel but I’d expect latest mainline to handle newer processors better than some of the older stable kernels in some of the more mainstream slower releasing distros.

Ran Asahi for several months, tried it out again recently. It’s good/fine, I just don’t love fedora.

There’s some funkiness with the more complicated install, the AI acceleration doesn’t work, no thunderbolt / docking station.

MacBooks are great hardware but I don’t think they’re the best option for Linux right now. If you’re never going to boot into macOS then I’d look for x13, new Qualcomm, isn’t there a framework arm64 option now or was that a RISC module?

I’m also assuming you’re not looking to do any gaming? Because gaming on ARM is not really a thing right now and doesn’t feel like it will be for a long while.