HAIrk: Difference between revisions

From NURDspace
No edit summary
No edit summary
Line 9: Line 9:
|Location=gpu.vm.nurd.space
|Location=gpu.vm.nurd.space
}}
}}
== What is this ==
There's so many fun networks now to run on GPUs! We wanted to share playing with them.
== How does it work ==
For now ; http://10.208.30.24:8000/
For now ; http://10.208.30.24:8000/


There's a queuing system in place, and soon it'll get hooked up through ghbot , maybe discord(?) and perhaps mediawiki(!!!)
There's a queuing system in place, and soon it'll get hooked up through ghbot , maybe discord(?) and perhaps mediawiki(!!!)


Maybe people can place some cool stuff they made here, and what configs they used? :)
# open webpage
# enter a prompt (this is a piece of text describing what you want to see , for example 'a digital artwork of a rake floating in cyberspace with many fragments of keyboards floating around , photorealistic , trending on artstation'
# click 'generate'
# wait ~45 seconds per queue item (you cant see queuesize yet)
# you get a picture \o/
 
Stuff to tweak ;
* ' cfg scale ' has some complexity addition to the generated image (see the reddit post somewhere below)
* ' steps ' is amount of iterations the model runs on top of itself to match your prompt, higher takes longer, but most samplers (default we use is KLMS) dont do well with <32 steps , notably k_euler_a DOES get some nice results for ~10 steps already, so if you're in a hurry ...
 
Another thing you can try is remixing original images with the 'img2img' features.
 
# open webpage
# enter a prompt for what you want to see the image become (for example 'trump raking the forest')
# next to 'img2img' click on 'choose file' , choose some trump.jpg , preferebly somewhat close to the prompt you want
# lowering 'img2img strength' will make it MORE the original picture (under 0.4 is usually nowhere near any changes, unless you use a high cfg scale?? see tips below)
# click 'generate'
# wait ~45 seconds per queue item (you cant see queuesize yet)
# you get a picture \o/
 
Please don't over abuse it :D
 
== Some tips ==
 
* https://mrdeepfakes.com/forums/threads/guide-using-stable-diffusion-to-generate-custom-nsfw-images.10289/
 
Stolen from that site (if you dont wanna click links with 'nsfw' in the url)
 
* You can drag your favorite result from the output tab on the right back into img2img for further iteration
* The k_euler_a and k_dpm_2_a samplers give vastly different, more intricate results from the same seed & prompt
* Unlike other samplers, k_euler_a can generate high quality results from low steps. Try it with 10-25 instead of 50
* If you have more Vram but are still forced to use the optimized parameter, you can try --optmized-turbofor a faster experience
* The seed for each generated result is in the output filename if you want to revisit it
* Using the same keywords as a generated image in img2img produces interesting variants
* It's recommended to have your prompts be at least 512 pixels in one dimension, or a 384x384 square at the smallest
* Anything smaller will have heavy artifacting
* 512x512 will always yield the most accurate results as the model was trained at that resolution
* Try Low strength (0.3-0.4) + High CFG in img2img for interesting outputs
* You can use Japanese Unicode characters in prompts
 
Maybe people can place some cool stuff they made here, and what parameters they used? :)
 
== Extra links ==
 
* Checkout the GPU stats in [[Grafana]] on https://metrics.nurd.space/d/tAe_RuWVz/erratic-gpu
 
There are many tutorials for this stuff around, not all as SFW, but still good:


Also checkout the GPU stats in [[Grafana]] on https://metrics.nurd.space/d/tAe_RuWVz/erratic-gpu
* https://mrdeepfakes.com/forums/threads/guide-using-stable-diffusion-to-generate-custom-nsfw-images.10289/
* https://www.reddit.com/r/StableDiffusion/comments/wnlsn8/steps_and_cfg_scale_tests/
*

Revision as of 17:20, 5 September 2022

hAIrk
HAIrk.png
Participants User:buzz
Skills software, neural networks, gpu
Status Active
Niche Artsy stuff
Purpose Fun
Tool No
Location gpu.vm.nurd.space
Cost
Tool category

hAIrk

HAIrk.png {{#if:No | [[Tool Owner::{{{ProjectParticipants}}} | }} {{#if:No | [[Tool Cost::{{{Cost}}} | }}

What is this

There's so many fun networks now to run on GPUs! We wanted to share playing with them.

How does it work

For now ; http://10.208.30.24:8000/

There's a queuing system in place, and soon it'll get hooked up through ghbot , maybe discord(?) and perhaps mediawiki(!!!)

  1. open webpage
  2. enter a prompt (this is a piece of text describing what you want to see , for example 'a digital artwork of a rake floating in cyberspace with many fragments of keyboards floating around , photorealistic , trending on artstation'
  3. click 'generate'
  4. wait ~45 seconds per queue item (you cant see queuesize yet)
  5. you get a picture \o/

Stuff to tweak ;

  • ' cfg scale ' has some complexity addition to the generated image (see the reddit post somewhere below)
  • ' steps ' is amount of iterations the model runs on top of itself to match your prompt, higher takes longer, but most samplers (default we use is KLMS) dont do well with <32 steps , notably k_euler_a DOES get some nice results for ~10 steps already, so if you're in a hurry ...

Another thing you can try is remixing original images with the 'img2img' features.

  1. open webpage
  2. enter a prompt for what you want to see the image become (for example 'trump raking the forest')
  3. next to 'img2img' click on 'choose file' , choose some trump.jpg , preferebly somewhat close to the prompt you want
  4. lowering 'img2img strength' will make it MORE the original picture (under 0.4 is usually nowhere near any changes, unless you use a high cfg scale?? see tips below)
  5. click 'generate'
  6. wait ~45 seconds per queue item (you cant see queuesize yet)
  7. you get a picture \o/

Please don't over abuse it :D

Some tips

Stolen from that site (if you dont wanna click links with 'nsfw' in the url)

  • You can drag your favorite result from the output tab on the right back into img2img for further iteration
  • The k_euler_a and k_dpm_2_a samplers give vastly different, more intricate results from the same seed & prompt
  • Unlike other samplers, k_euler_a can generate high quality results from low steps. Try it with 10-25 instead of 50
  • If you have more Vram but are still forced to use the optimized parameter, you can try --optmized-turbofor a faster experience
  • The seed for each generated result is in the output filename if you want to revisit it
  • Using the same keywords as a generated image in img2img produces interesting variants
  • It's recommended to have your prompts be at least 512 pixels in one dimension, or a 384x384 square at the smallest
  • Anything smaller will have heavy artifacting
  • 512x512 will always yield the most accurate results as the model was trained at that resolution
  • Try Low strength (0.3-0.4) + High CFG in img2img for interesting outputs
  • You can use Japanese Unicode characters in prompts

Maybe people can place some cool stuff they made here, and what parameters they used? :)

Extra links

There are many tutorials for this stuff around, not all as SFW, but still good: