oooh, for 40 GB of VRAM?
oooh, for 40 GB of VRAM?
Fyep
Fgo tier 3
Frank 3
Fyou do flux right?
Ethat's explain a lot... hehe, okey, thanks! no, Trying to train SDXL
Ethe configs are only for flux?
Fi have different configs for each
Ffor sdxl use onetrainer it is bestr
Fyou using kohya or onetrainer?
Fi will link you accurate file
Eonetrainer
Fkk
Egotcha, thanks
FPatreon
Get more from SECourses: Tutorials, Guides, Resources, Training, FLUX, MidJourney, Voice Clone, TTS, ChatGPT, GPT, LLM, Scripts by Furkan Gözü on Patreon
Fuse tier1_15.4GB_fast_v4.json
Fthis is for sdxl
Fuse reg imags hugely improves for training a person
MThere it is, that was my second question. So you actually do prefer OneTrainer, at least for SD* models…
Fsd trainer really does handle vram better
Falso it is all in one
Fwith kohya we have gui and scripts
FHello together,
have anyone trained multiple concepts in one or more dreambooth training(s)?
I want to train 2 different characters with unique tokens into my model and face the issue that the one concept is always bleeding into the other.
I tried to remove the class token and made several tests with a combined training set and single trainings. Unfortunately no success. Each character has a versatile dataset of 35 high quality images.
Any idea to reduce the bleeding?
have anyone trained multiple concepts in one or more dreambooth training(s)?
I want to train 2 different characters with unique tokens into my model and face the issue that the one concept is always bleeding into the other.
I tried to remove the class token and made several tests with a combined training set and single trainings. Unfortunately no success. Each character has a versatile dataset of 35 high quality images.
Any idea to reduce the bleeding?
Fi just replied on youtube but it may not be possible since FLUX has internal text encoding. so it knows both are man. however you can try this. only ohwx and bbuk as rare token and use clip text encoder training that i added yesterday
Fstill may bleed. fine tuning may solve though not sure
FSorry for the missing information. I talk about a SDXL Model 
Fyes people said they do very good. are you doing lora or fine tuning?
FI fine tune the model with character images.
Lora training works great with your guides.
Lora training works great with your guides.
Fare you using onetrainer?
FI used OneTrainer (with your config) and dreambooth from kohya_ss also with your configuration
Fi see you tested on both
Fand still bleed?
FYes, onetrainer was much worse than kohya for some reason.
I made also dataset tagging with following schemas:
-> <unique identifier>
-> <unique identifier > <class token>
-> <unique identifier>, <describing image without character attitudes >
I made also dataset tagging with following schemas:
-> <unique identifier>
-> <unique identifier > <class token>
-> <unique identifier>, <describing image without character attitudes >
FTo test if the tagging is influencing common model tokens like men or women
Fare you using reg images?
Freg makes huge impact on onetrainer
Fand which base model you are training sdxl base?
FIt’s a customized pony based model for a client.
I didn’t use reg images.
I didn’t use reg images.
FDid also a run on the base pony to verify model issues on my side.
Fis the reason i bet
Fit is very different
Ftry on real vis XL 4
FO.k I didn’t think that could make such big problems.
I will make a training on sdxl base model and realvis.
Thank you for your help. It let me hope to find the problem source
I will make a training on sdxl base model and realvis.
Thank you for your help. It let me hope to find the problem source
Swhat is the best upscaler for hires.fix?
Fsupir is best
Shmm is that an extension i have to download?
Fit is different
S
FYouTubeSECourses
In this video, I explain how to 1 click install and use the most advanced image upscaler / enhancer in the world that is both commercially and open source available. The upscaler that I am going to introduce you is open source #SUPIR and the model is free to use. SUPIR upscaler is many times better than both paid Topaz AI and Magnific AI and you...
