It is not really a problem, I need them in Blender, so my workflow is still ImagesToPlanes with png
It is not really a problem, I need them in Blender, so my workflow is still ImagesToPlanes with png's^^
Cyou need them in blender?
AHave only an old 3080 mobile here, (~3070 desktop) but with 16GB VRam.
Chow are you running blender on that?
Csolving this is the holy grail problem for flux at the moment, I don't know if there is a case to be made for woman + man training being distinct enough classes for it to work, but the same class always seems to fail
Cflux isn't trainable, keep that in mind
Ci ran blender on a 3gb 1060 for years, wireframe or solid mode in viewport are fine enough
Ayep - I do a lot of technical presentations and I am using some of our staff to explain our systems 
Cwings3d might do just as good a job, and need a lot less resources than blender
AI'm using Blender now since 2018, dropped modo for it, no problems with 4k or 8k renders
Cwell i am not fussed on the definition of training in any strict sense, you can input data and then reliably output based on that data, whatever you want to call it it was 'trained' to deliver results. That is just for my purposes though, whether its good bad or terrible under the hood is largely irrelevant to me I just want some cool picture for some dopamine
Cyou'll get 'something' - however the reason you are running into errors and issues that you can't fix with training is becase flux is not trainable. it's rigid, inflexible, while you might succeed in creating something that'll paint your face on an image, that's not what Loras are actually for, or fine tuned check points. and so most of what will happen is that the training will fail
A
C i like blender too - but i wouldn't even consider running the current version of it on something less than a 4090AWhy? I'm using Blender 4.2 and 4.3 on a daily basis.
AAnd I have scenes with 80mio+ verts ....
AIt is about knowledge + tech. Like everywhere
C80mil verts hnnnngh
AYep. in such heavy scenes I'm using camera culling. Important if you have large landscapes with graswald objects + forestation trees + alpha trees in the regions far away.
Cwe use single sided image planes for that stuff
AYep, that's alpha trees + triplanar shaders.
Fwell normally you should be able do with minimal invasion. however with FLUX it is very easy to get broken. so not working atm
Fbut with SDXL if you properly train with reg images it should work decent
Fhowever quality of FLUX is many levels better
AThanks - it seems I might have misunderstood your posts then.
AI was the opinion Dreambooth is finetuning the model itself.
AWhat is the result then if I use dreambooth instead of the lora creation?
A(Or the AI toolkit...)
AI refer to your patreon post: Kohya FLUX Fine Tuning (Full Checkpoints) Training Full Tutorial For Local Windows and Cloud RunPod and Massed Compute
New
9 hours ago
New
9 hours ago
AI was the opinion I get a new checkpoint after the training
CYou will have a new checkpoint which you can use instead of the base model you trained on, or you can extract a lora from it to use in combination with the base model, but it will still have turned every 'man' into some version of you (if you were training yourself)
Fdreambooth / fine tuning way better than lora
Fcurrently we use dreambooth tab but we are doing fine tuning
Fsince we dont use any reg images
AWill try to get it running.
CI attempted using the 24gig config file for finetune on my 4090 but it estimated around 700 hours.. is this normal?
Fnope you must be using shared vram.
Fincrease number of blocks to swap or reduce your vram usage
Falso make a fresh kohya installation if still fails
CI basically force quit everything I could except kohya. It is a fresh install
Fi tested and even on my RTX 3060 works great :d
Fso how much VRAM used before starting did you check?
Caround 0.6
CI do suspect something else on my system or hardware though. Even running base flux1-dev in forge is super slow.
Fi think should work
Ftry 16 gb config
Fand report me back speed
Cwill do, thank you
Falso check how much shared vram used
Falways a possibility