so I can't combine my own flux finetuned model with the depth or canny modls?
so I can't combine my own flux finetuned model with the depth or canny modls?
Fi made huge improvement to idm vton app
Fgonna update
Fsadly not. you can use their loras but especially canny lora so bad
MOk I get it, thanks
Fnew idm vton published with new features
FPatreon
Get more from SECourses: FLUX, Tutorials, Guides, Resources, Training, Scripts on Patreon
Vhttps://ia.acs.org.au/article/2021/police-mistake-bitcoin-mine-for-cannabis-farm.html
maybe they mistake you for a grower
also is your computer cloud or local computer? If local then I guess its getting pretty hot in that room
maybe they mistake you for a grower
also is your computer cloud or local computer? If local then I guess its getting pretty hot in that room
Information Age
Raid on suspected hydroponic setup uncovers illicit mining operation.
V@Furkan Gözükara SECourses what would be the way to kind of automate the flux finetuning process more? is there a way to create an image that has fixed flux version etc that you can just load up on cloud computer?
this would not be possible with massed compute?
with runpod?
or is there a way to make this more automated.... not exactly sure how... but maybe with lambda from AWS? any idea?
this would not be possible with massed compute?
with runpod?
or is there a way to make this more automated.... not exactly sure how... but maybe with lambda from AWS? any idea?
Fautomate = software development skills or $$$$$
Vhaha... yeah I got a computer science degree and cloud certification but not sure yet which are the plattforms or tools to use.... so can tell me which are the suited plattforms for quick protoyping, also cheap would be good.... because it seems massed compute is cheapest but has super limited resources and you cannot upload prebaked images? Didnt have a look at how runpod works yet... Before somebody mentioned somehting about "replicate"....
I mean I could create an image for AWS instance.... then add api gateway, lambdas etc... but I have to look actually how much these gpus cost on AWS platform directly... will have a look tomorrow regarding pricing...
but then I would need to create some kind of application with api running on the aws instance which then creates the images etc...
but not sure yet which are the plattforms or tools to use.... so can tell me which are the suited plattforms for quick protoyping, also cheap would be good.... because it seems massed compute is cheapest but has super limited resources and you cannot upload prebaked images? Didnt have a look at how runpod works yet... Before somebody mentioned somehting about "replicate"....I mean I could create an image for AWS instance.... then add api gateway, lambdas etc... but I have to look actually how much these gpus cost on AWS platform directly... will have a look tomorrow regarding pricing...
but then I would need to create some kind of application with api running on the aws instance which then creates the images etc...
Fi never researched to be frank
Vhmmm... yeah maybe the replicate api... then combine it with some other things... I guess there are also some turnkeysolutions for user interfaces.... Need to look a bit more
from replicate:
Nvidia L40S GPU (gpu-l40s, $3.51/hr)
Nvidia A100 GPU (gpu-a100-large, $5.04/hr)
but it says the api use is billed per second
from replicate:
Nvidia L40S GPU (gpu-l40s, $3.51/hr)
Nvidia A100 GPU (gpu-a100-large, $5.04/hr)
but it says the api use is billed per second
VActually somebody saw the pictures I generated with the flux and wants me now to create some images for him for money so yeah....
RHey Doc, I just saw the IDM VTON app. Have you compared IDM VTON with CAT VTON and/or Flux Redux?
Fye people using replicate
Fi havent compared with cat vton yet
Fflux redux works different
NYou want to share?
I'll be sure to test it
And here's a question, has
https://huggingface.co/spaces/tencent/Hunyuan3D-2/tree/main
I'll be sure to test it
And here's a question, has
Hunyuan3D-2 been deployed yet? Who knows can advise solutions for 4090rtx? https://huggingface.co/spaces/tencent/Hunyuan3D-2/tree/main
�Kohya implemented this - https://github.com/kohya-ss/sd-scripts/pull/1864 can you please tell me how to start this in kohya. It will be a great factor to analyze how the lora or dreambooth is training.
GitHub
Related #1856 #1858 #1165 #914
Original implementation by @rockerBOO
Timestep validation implementation by @gesen2egee
Updated implementation for sd3/flux by @hinablue
I went through and tried to m...
Original implementation by @rockerBOO
Timestep validation implementation by @gesen2egee
Updated implementation for sd3/flux by @hinablue
I went through and tried to m...
Jtrying to generate 4 images at the same time (using 4 L40) but it seems like it will only make 2 at a time?
If I leave OverQueue=1 (default) then 2 will generate exactly the same time, and then the next 2.
If I set OverQueue=0 then it still takes about 40 seconds before the fourth image starts to generate, so ends up taking just as much time. Like the first photo will be finished before the fourth one starts.
Shouldn't all 4 photos just start generating at the same time?
If I ask to generate 8 images at the same time, all 4 GPU's will run from the start like it should though...
On Massedcompute.
If I leave OverQueue=1 (default) then 2 will generate exactly the same time, and then the next 2.
If I set OverQueue=0 then it still takes about 40 seconds before the fourth image starts to generate, so ends up taking just as much time. Like the first photo will be finished before the fourth one starts.
Shouldn't all 4 photos just start generating at the same time?
If I ask to generate 8 images at the same time, all 4 GPU's will run from the start like it should though...
On Massedcompute.
Ttry looking at debug logs
Jah yea should've sent that. forgot to look and have closed down now
PHi guys, I'm testing a new upscaler technique and I'd like your opinion on the result, what do you think? I'm going to send 2 images, one in 1024x768 and the other in 4096x3072 upscaler.
P
P
Tlooks decent
TDoes anyone use KLING AI paid memberships?
I was looking to get yearly sub, but they change the deal dramatically just over the course of a day removing daily log in credits (which is basically x2 potential monthly generations)
The reviews on reddit also indicate that the support is non existent and many people face problems with one sided deal changing and zero communication with clients
I was looking to get yearly sub, but they change the deal dramatically just over the course of a day removing daily log in credits (which is basically x2 potential monthly generations)
The reviews on reddit also indicate that the support is non existent and many people face problems with one sided deal changing and zero communication with clients
TAs for quality Kling AI 1.6 seems to be the best img2vid model publicly available as of now
TClosest competitors hailuoai and sora currently seriously behind
Ait's the best currently what do you mean they actually did remove ??
AI suppose their abusing monopoly until a competitor who comes beat them
GHi @Furkan Gözükara SECourses,
I've tried both
on 48 images with faces pre-captioned with joy captioning and replaced with
it takes too much time - estimated 45 days! is that make sense??
Shared GPU raised to 14.2 and GPU RAM is on 7.5 GB.
I've attached all screenshots
I've tried both
flux1-dev-fp8.safetensors and flux1-dev.safetensors based on 8GB_GPU_Quality_Tier_4_FP8_6850MB_13.2_Second_IT.json configon 48 images with faces pre-captioned with joy captioning and replaced with
ohwx token,it takes too much time - estimated 45 days! is that make sense??
Shared GPU raised to 14.2 and GPU RAM is on 7.5 GB.
I've attached all screenshots
Ganother screenshot with more lines from training console
Fi will share hopefully after finalizing
VHi, I also have a problem when training with kohya: I have a geforce rtx 3900 with 24 vram, I use the models from your youtube tutorial video (flux dev, fp16, etc.etc). Before training, I clear vram (restart, autostart apps off, etc). When I check, I have enough vram under 500 mb. When I start training, it goes up to 23 GB and ALSO the shared Vram goes up. Why? Is that normal? using the 24GB_GPU_Quality_Tier_3_23150MB_5.9_Second_IT
Fi dont plan to research this atm
Fclick load model
Fit will then use all 4
For generate like 16
Fyour folder repeating is 40
Ftherefore you are doing 392k steps
Fmake folder name like 1_ohwx man
Fyour speed is good
F10 second / it
Ftotally normal
Fyou can increase block swap count
Fand compare speed
�Okay but can you tell me how I can run this in kohya? I am not able to understand.
Vokay. thanks. it trains like 6-7 hours
