I heard that onetrainer is 2x faster on flux training
I heard that onetrainer is 2x faster on flux training
Dbut there is some incompatibility with forge, is diferent lora format, and to train you need flux models on diffusion format
Dthe forge incompatibility will be fixed sood, by onetrainer or by forge idk really
JFixed this morning: https://github.com/lllyasviel/stable-diffusion-webui-forge/commit/44eb4ea83797b2abcc2dcc3e0bfcbed77e5f7a6e
GitHub
requested by #1727
and some cleanups/licenses
PS: LoRA request must give download URL to at least one LoRA
and some cleanups/licenses
PS: LoRA request must give download URL to at least one LoRA
BHello, I am working on fine tuning on stable diffusion xl and I am using my own interface. I have a couple of problems. I want to limit the number of colors the user wants. For example, if the user chooses 5 colors, the model should use only 5 colors can be less. The other problem is the tiling process. There are a few problems in this too. I would be happy if you help.
Fjust impossible with same config
Swhat is best quality in flux.dev: 1024x1024 +upscale or generate in 2048x2048 native?
Sor I mean what gives best image quality, what resolution flux.dev is supposed to be used at if generation time is no problem
Fi dont know if it can do perfect 2048
Fi think compare
Fcurrently i generate 1024 and upscale with supir
Fmost realistic dinasasur :d
Aanybody knows why i can't connect my seed output from rgthree with the seed input from ksampler(was)?
Feven with T5 training captions yields lower quality
Abest way to travel 
Fyep 
MYou are getting better results when you train without captions?
Fi will post on patreon and reddit
Mone more thing there is no point in checking Apply T5 Attention Mask when you are training without captions right?
Fi think iy very slightly improves
Falso with T5 training i think unet can go lower
Fit brings some quality
Fbut in some images resemblance is lost
Fso it is a choice
Fi am analyinz
M@Dr. Furkan Gözükara T5 is mainly for text trainings, t5 not worth training at all
Mi did about 60+ trainings with it
Mit'll work amazing if you're training text
Fwhat do you train text
Fwith cpu offloading it uses 23.34 gb
F24 gb may train
Fand 22.44 gb
Fsecondary config
Mkohya mentioned to me in dms.
Mhes added different learning rates for t5 and clip l
Mso he said you'll need to lower t5
to 1e-7 or 1e-6
to 1e-7 or 1e-6
Factually even 05-05 even didnt cook the model at all
Fi mean the T5
Falthough i didnt do text training
Fi compared ohwx man vs full captioned
Mt5 wont do much for people training
Mt5 is a text to text model.
you may get better results adjusting the clip l
kohya suggested to me having clip l 1/10
so for your config unet 5e-05
clip l 5e-06
you may get better results adjusting the clip l
kohya suggested to me having clip l 1/10
so for your config unet 5e-05
clip l 5e-06
Fi tried every clip LR already :d
Mbut then again you're only training with ohwx man so it wont do much
Fi tried full joy captions too
F300 tokens
Mnot worth it, if you're training that many tokens you need to lower all your rates and train for a long time
Fbut may depends on dataset
Fi will focus on fine tuning
