I recommend a used 3090, as that has 24 GB of VRAM and generally can be found for $800ish or less (at least when I last checked, in February). It’s much cheaper than a 4090 and while admittedly more expensive than the inexpensive 24GB Nvidia Tesla card (the P40?) it also has much better performance and CUDA support.
I have dual 3090s so my performance won’t translate directly to what a single GPU would get, but it’s pretty easy to find stats on 3090 performance.
The above post says it has support for Ollama, so I don’t think this is the case… but the instructions in the Readme do make it seem like it’s dependent on OpenAI.
16 GB of RAM, though? Is it even optimized for the Ryzen 9950X3D?
And a 4 TB SSD - not even necessarily NVME?
Doesn’t seem high powered to me.
Are you saying that NAT isn’t effectively a firewall or that a NAT firewall isn’t effectively a firewall?
Is there a way to use symlinks instead? I’d think it would be possible, even with Docker - it would just require the torrent directory to be mounted read-only in the same location in every Docker container that had symlinks to files on it.
Depending on setup this can be true with Jellyfin, too. I have a domain registered, use dynamic DNS, and have Traefik direct a subdomain to my Jellyfin server. My mobile clients are configured using that. My local clients use the local static IP.
If my internet goes down, my mobile clients can’t connect, even on the LAN.
Orcas are dolphins, though. Do you mean bottlenose dolphins specifically?
Further, “Whether another user actually downloaded the content that Meta made available” through torrenting “is irrelevant,” the authors alleged. “Meta ‘reproduced’ the works as soon as it made them available to other peers.”
Is there existing case law for what making something “available” means? If I say “Alright, I’ll send you this book if you want, just ask,” have I made it available? What if, when someone asks, I don’t actually send them anything?
I’m thinking outside of contexts of piracy and torrenting, to be clear - like if a software license requires you to make any changed versions available to anyone who uses the software. Can you say it’s available if your distribution platform is configured to prevent downloads?
If not, then why would it be any different when torrenting?
Meta ‘reproduced’ the works as soon as it made them available to other peers.
The argument that a copyrighted work has been reproduced when “made available,” when “made available” has such a low bar is also perplexing. If I post an ad on Craigslist for the sale of the Mona Lisa, have I reproduced it?
What if it was for a car?
I’m selling a brand new 2026 Alfa Romeo 4E, DM me your offers. I’ve now “reproduced” a car - come at me, MPAA.
The president won [the] popular vote
Only if you ignore the huge amounts of voter suppression. If you don’t, then he lost the popular vote and the electoral vote - netting 45.8% of the popular vote to Kamala’s 52.7%, and he earned at most (and probably less than) 252 electoral votes to Kamala’s 286.
If you’re in the US, automatic is fine. Manuals make up like 1 percent of new cars and maybe 4% of used cars here. It doesn’t hurt to know how to drive one, but it doesn’t benefit you much, either. I drove a manual once, but it was a rental in another country. I’ve never been faced with needing to - or even having the opportunity to - drive a manual in the US.
However, learning on a manual does make it easier to understand certain ways of how cars work, even on automatics (less so on CVTs), so if you like understanding things more, I recommend manual even in the US. You can still get that understanding driving automatics, though - just a bit more effort.
Outside the US, most places I know of manual is the default. If manuals make up even 30 percent or so of cars where you live, I strongly suggest learning to drive one.
Even with an HOA, you can still end up needing to pay tens of thousands for surprise repairs in the forms of special assessments, especially if the HOA is poorly managed.
I attended a 1-on-1 meeting that a billionaire scheduled with me but that they themselves did not attend.
Under notes, where you said my name, did you mean “Hedgedoc?”
If your recommend protein intake is 70 grams per day (meaning you weigh about 195 pounds / 87 kg) and you’re only getting 20 grams per day, then you are likely already experiencing health issues.
From https://www.verywellhealth.com/protein-deficiency-symptoms-8756264 you could expect to experience:
Not all of those are immediately noticeable.
However, I’m with the other commenter who said that they think it’s likely that you’re under-estimating your daily protein intake. What method did you use for tracking and calculating it?
From the feature comparison at https://github.com/meichthys/foss_note_apps only two FOSS apps support handwriting: Joplin (with a plugin) which gets a subjective 6/10 score, and TriliumNext, which gets a subjective 2/10 score. I personally dislike Joplin but many people love it, so I recommend giving it a shot. EDIT: I installed Joplin using the APK from the site and both the handwriting and Excalidraw plugins were “not available on mobile,” so I have to rescind my recommendation. On my iOS device, the plugins didn’t even show up in the search.
I think TriliumNext is great, but the mobile experience is still lacking (though they are tracking several issues to improve here). There’s no dedicated mobile app but they at least have a PWA. It also needs to be self-hosted, but doing so is straightforward if you’re already using Docker. The handwriting is done via a built-in Excalidraw integration.
Here are some options not captured in that list:
Obsidian is not open source, but also has an Excalidraw plugin. I’ve not used it yet but I’ve seen multiple discussions saying that it’s very well done and has additional functionality on top of base Excalidraw. There’s also an open source (MIT) plugin for Obsidian that adds support for handwritten notes. I only use Obsidian on my work computer and haven’t used it either, though I plan to install the Excalidraw plugin Monday.
StylusLabs Write is FOSS (AGPL 3.0), multiplatform, and has a free Android apk available. Note that the Google Play version has had updates suspended. I just learned about it and don’t know how it otherwise measures up. I’m planning to check it out, though.
You can use any note app that has Excalidraw support, so long as you don’t need your handwritten text to be OCRed. That means that the following are all options:
local docker hub proxy
Do you mean a Docker container registry? If so, here are a couple options:
At that point, you could say “male characters.”
Oh 100% agreed - in this instance, it’s clear that OBS has a well maintained package that should be prioritized. But they could keep their repo first and remove OBS (and other known-to-be-well-maintained apps) from it to accomplish that.
They put their repo first on the list.
Right. And are we talking about the list for OBS or of repos in general? I doubt Fedora sets the priority on a package level. And if they don’t, and if there are some other packages in Flathub that are problematic, then it makes sense to prioritize their own repo over them.
That said, if those problematic packages come from other repositories, or if not but there’s another alternative to putting their repo first that would have prevented unofficial builds from showing up first, but wouldn’t have deprioritized official, verified ones like OBS, then it’s a different story. I haven’t maintained a package on Flathub like the original commenter you replied to but I don’t get the impression that that’s the case.
Look up “LLM quantization.” The idea is that each parameter is a number; by default they use 16 bits of precision, but if you scale them into smaller sizes, you use less space and have less precision, but you still have the same parameters. There’s not much quality loss going from 16 bits to 8, but it gets more noticeable as you get lower and lower. (That said, there’s are ternary bit models being trained from scratch that use 1.58 bits per parameter and are allegedly just as good as fp16 models of the same parameter count.)
If you’re using a 4-bit quantization, then you need about half that number in VRAM. Q4_K_M is better than Q4, but also a bit larger. Ollama generally defaults to Q4_K_M. If you can handle a higher quantization, Q6_K is generally best. If you can’t quite fit it, Q5_K_M is generally better than any other option, followed by Q5_K_S.
For example, Llama3.3 70B, which has 70.6 billion parameters, has the following sizes for some of its quantizations:
This is why I run a lot of Q4_K_M 70B models on two 3090s.
Generally speaking, there’s not a perceptible quality drop going to Q6_K from 8 bit quantization (though I have heard this is less true with MoE models). Below Q6, there’s a bit of a drop between it and 5 and then 4, but the model’s still decent. Below 4-bit quantizations you can generally get better results from a smaller parameter model at a higher quantization.
TheBloke on Huggingface has a lot of GGUF quantization repos, and most, if not all of them, have a blurb about the different quantization types and which are recommended. When Ollama.com doesn’t have a model I want, I’m generally able to find one there.