Ok thank you. Will you dive into more product/object specific (lora) training experiment/tutorials i
Ok thank you. Will you dive into more product/object specific (lora) training experiment/tutorials in the future you recon?
Fi may make but too many jobs waiting i need to research sd 3.5 
Fcurrently testing model varients impact on lora
Fand lora extraction
Fto post on civitiai
DHaha makes sense! We'll keep following your work closely, thanks!
T@Furkan Gözükara SECourses Is there any reason to use kohya over OneTrainer quality-wise for Flux? Is it easy to convert your best koyha config settings to OneTrainer? Also noticed onetrainer supports SD3.5 There are some nice Quality of life things in Onetrainer, like dynamic save anything ondemand, resume from backup, changing samples during training, sample on demand etc. thoughts?
WKohya have most of your thing but you need to learn how to do it. I use Kohya since SD 1.5 never feel that I need to use OneTrainer. Koyha maybe a bit more technical but when you understand it, it's very versatile
TI like Kohya, it just needs some of the quality of life things. like save now.. easy resume, change sample prompts. So many times i want to use GPU for something, but have to wait 20 epochs 
would be nice to have a bit more control..
would be nice to have a bit more control..FKohya also supports 3.5 . also you can convert my configs
FOneTrainer was lacking previously
Fhopefully I will compare and publish configs
Wbut I need to study again for someone who already know SD for a year or more, people tend to become more lazy especially when Onetrainer does not have something extraordinary than Kohya and also very few people like @Furkan Gözükara SECourses who dedicate time to study Kohya. Finding the right config for lora training or fine tuning is really time consumption and require deep knowledge about AI programming
Fyou can clone our kohya configs to onetrainer i did it for sdxl and sd 1.5 :d
Wreally, how about training speed Kohya vs Onetrainer
Fi havent compared yet but kohya also just made a branch to speed up fine tuning
ZCould you get in touch with me so we can discuss this?
TIs this included in your new v11 zip what is the difference? Do I need to upgrade?
Fnot included yet
Fi need to test first
Fbut upgrade it helps me :d
Walready messsage for you
Fis it worth training on higher resolutions then 1024 x 1024 ? lets say like 3k? 4? comething like 3000 x 2000 ? Thanks
Flast time i tested i didnt see benefit
FHello again,batch 7 at 250 images on my 4090 is suuuuuper slow
F
Fwas able to spin a 250 last night
Fwhat am I missing?
Fmessage.txt14.16KB
FUsing the 24G config file for dreambooth training
Ftrying to train a person
F
Fany help super appreciated
Fbatch size 7 is for 48 gb gpus
Fyou should use batch size 1 config
Ffor 24 gb gpus
F24GB_GPU_23150MB_10.2_second_it_Tier_1.json
FOh I see
Fthank you
Fby the way kohya made update
Fhopefully it will become even faster
Fi havent tried yet
FWill try it on the next one
Fit is not merged into main branch yet
FOh, OK, thanks
1so.. I've been training on massed_compute recently (A6000) but thought I'd give my 4090 a test. I'm actually quite suprised at the performance using the 24GB_GPU_23150MB_10.2_second_it_Tier_1.json
1fresh install of Koyha.
Frtx 4090 will be faster than a6000 with newest update - not merged into main yet :d
Ffor fine tuning
AWhat is the fastest kohya config to use if you have 80GB vram? (H100)
Fbatch size 7 flux fine tuning