old but relevant, it's like a production system. We can continue to tune and squeeze 1mp pictures out of it in high quality on relevant localized hardware without breaking a sweat. 1-3 seconds on a m3 system, and then cascade of tooling below stays the same.
SV_BubbleTime 41 minutes ago [-]
A1111 also had its time. Comfy takes a couple hours to learn, and then it’s vastly superior. Like, if you are already on Mac there is no reason to also kick yourself in the face trying to go back to 1111.
qclibre22 25 minutes ago [-]
There's also sdcpp ( https://github.com/leejet/stable-diffusion.cpp ) . It is for people that know command line shells like bash or Powershell. SDCPP is like llama.cpp but it is for using text to image AI models. Not everyone likes the node/graph programming interface in Comfy or a Webpage interface. Some people need these GUI/web interfaces and get lost and frustrated in shell scripting.
dmikeyanderson 10 minutes ago [-]
Totally and sdcpp and drawthings were inspiration for this work. It's not just about the UI, there's a whole stack of plugins, APIs etc. It would be a bigger shift, than just use other UI. Composition etc.
Plus this was fun to learn where the attention and time spent is eating up. I plan to git into the UNet, and then do some Multi-Model Memory Attention tuning as well, for Refining and Inpaint Swaps for the 8Gb Macs.
jurgenburgen 2 hours ago [-]
Trigger warning: AI content.
trencedamp 30 minutes ago [-]
If anyone is triggered by AI content they surely avoid HN
IronWolve 46 minutes ago [-]
Automatic1111 wasnt being updated, people moved to Forge Neo, ComfyUI and Maestro.
dmikeyanderson 12 minutes ago [-]
Yup! It was a fun experiment though!
Der_Einzige 9 minutes ago [-]
What a crazy repo. Some cyber archeologists need to do a case analysis of the entire diffusion model ecosystem circa the original Stable Diffusion up to now.
smallerize 56 minutes ago [-]
The speedup includes running LoRAs, right? Which ones are you using?
dmikeyanderson 12 minutes ago [-]
Yes it includes LoRA composition as well, a bunch from the internet, and they work just fine!
Plus this was fun to learn where the attention and time spent is eating up. I plan to git into the UNet, and then do some Multi-Model Memory Attention tuning as well, for Refining and Inpaint Swaps for the 8Gb Macs.