Put Codex to work on deploying it now, hoping the speed can improve quite a lot :-) Thanks anyway
That's crazy, a RTX Pro 6000 does that in in 2-3 minutes (give or take, depending on your exact settings). LLMs don't make the difference between standalone GPU vs unified memory + CPU so obvious as diffusion models seems to do.
Seriously, very dumb model compared to what you can run locally, but holy moly is it FAST on one GPU, seriously impressive. Can't wait for those to be scaled up a bit to fit perfectly within 96GB VRAM, then they'll be competitive.
> On the 128 GB M5 Max, clean end-to-end image+audio and embedded-video+audio renders completed in 74.58 and 76.99 seconds respectively, each with about a 40.1 GB peak physical footprint and zero swaps.
Looks like it uses 40GB? So your 96GB mac setup should work fine i guess (Model itself is 33B)
Anyway, good input!
> This misconstruction is very common, included in print publications spanning several centuries. It might be considered an alternative spelling, albeit still a mistaken usage.
Thanks though, I never actually knew so was helpful :)
Google Books search for the misspelling returns notwithstanding. A forced search for the misspelling shows nearly all of the errors are reprints of low quality lawsuit text, with one or two prose errors - not sure who is reading bad lawsuits in book form. Zero examples spell it as "non-with-standing".
The wiktionary definition reads like a student got bad marks and raced to add it to wiktionary to argue with their teacher. The only other "dictionary" with the definition is quoting this one. Even that drops the feeble "might be considered an alternative" claim. It isn't.
2) Since it's unified memory, you won't have 96GB available.
3) I offered a solution that is usually recommended to the "gpu poor", if he's concerned with how much memory he would need.
4) I stated, that people already pointed out how he should be fine and that "gpu poor" doesn't apply to him.
5) "gpu poor" depends on what model you are trying to use. If you want to run Kimi or GLM you are still "gpu poor" even if you have an RTX Pro 6000 with 96GB of VRAM.
I noticed on a bar TV the other day that some of the Chromecast screensaver landscape photo credits were to Peter Norvig. They were really lovely pictures.
What are some adult entertainment workflows in comfyui, I need best loras, best prompts to start with
and the communities, are they on telegram or something?
I’d personally steer clear of messaging platforms for this - who knows what one might stumble into there
Personally I have no interest, but sometime browse stuff out of curiosity. But this got more of my curiosity, what kind of "stuff" are you implying they might stumble upon on the open, public internet? Sure, some NSFW, horror and otherwise weird stuff is there, especially around AI generation, but hardly something that will leave you traumatized, unless I misunderstand what you're implying?
I had to modify the default ComfyUI workflows to use a GGUF quant (city96's ComfyUI-GGUF custom node, UnetLoaderGGUF in place of the stock loader) [0].
I use the model labeled Q5_K_M. There is Q8_0 available as well, which is 34GB and fits fine in 64GB unified memory if you keep resolution modest.
The main issue is speed, a ~9-second 480x864 clip at 20 steps takes me a bit over an hour. So this will be cool to try for the speed up alone.
There's a lot of great information and workflows available to follow on the r/StableDiffusion subreddit.
[0] https://huggingface.co/Abiray/MiniMax-H3-GGUF/tree/main/unet
that's rough. for comparison, i tried the exact same parameters on my 5090 RTX and it took 2 minutes to generate.
i believe diffusion models are primarily compute bound so the macs aren't really the ideal hardware for this kind of stuff