5 ms·
Okay... what's the downside?
by Filligree 3y ago
Okay... what's the downside?
- refulgentis 3y agoIn terms of, what's the tradeoff for the time decrease? Apples to oranges, they're comparing 11 hours on a Raspberry Pi Zero to: - 10 seconds on Intel i7-13700 - 3 seconds on Intel i9-9990XE - 5 seconds on Ryzen 9-5900X Additionally, the 2048 is accomplished by using RealESRGAN to 2x, which isn't close to what a native 2048 diffuser's quality would be. It does look interesting and is an achievement, in terms of, it's hard to write this stuff from scratch, much less in pure C++ without relying on GPU.
- Filligree 3y agoAh. I use RealESRGAN (or one of its descendants, rather) as a first pass upscaler before high-resolution diffusion. If you skip the diffusion step, of course it'll be faster.
- leonidasv 3y agoUnrelated, but now I'm curious about how much would it take on RPis 4 and 5.
- refulgentis 3y agoyeah me too...I've been very negative about the edge, it got overhyped with the romanticization of local LLMs, but there's a bunch of stuff coming together at the same time...Raspberry Pi 5...Mistral 7B Orca is my 20th try of a local LLM...and the first time it handled simple conversation with RAG. And new diffusion, even every 2 hours, is a credible product, arguing about power consumption aside...
- biomcgary 3y agoAlso $29 to get pre-trained model assets to run code.
- smusamashah 3y agoWhy does this one needs pretrained models? Can't we use any of the thousands of already available ones?
- TeddyDD 3y agoHard to tell since there is zero documentation in regard to models.
- brucethemoose2 3y agoThese are mostly Stable Diffusion architecture models, but its not the only game in town.