18000 steps is a lot, you may want to try earlier checkpoints
18000 steps is a lot, you may want to try earlier checkpoints
Tyou may also try different prompt engineering, generate a lot of images and cherrypick from them secondary dataset to include in traning of second gen model with more stilyzed images in training data
Myes I did it
MI did imagine that. But I watched @Furkan Gözükara SECourses tutorial and saw that he had some incredibly stylized images... I think he also only trained with realistic images. That's where my doubt comes from
Fyes buyt i never tried
Fits option is here
F
Fyes flux is very realistic
Ftherefore i recommend 2 step training for stylized images
Ffirst train, generate some good stylized images, and retrain on them
Fi had 256 images and dataset was variety . also still i had hard time and needed to find prompts 
Mthank you sir!
FThe grid test I am analyzing to find newer FLUX DEV training. This is not even including the first 10 different trainings i made 
1176 images. I think we gonna have a better workflow than what we have with using more VRAM and more training time.
1176 images. I think we gonna have a better workflow than what we have with using more VRAM and more training time.
RIn case someone is interested in creating LoRAs from Lumina2: https://huggingface.co/sayakpaul/trained-lumina2-lora-yarn, https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_lumina2.md (the code).
GitHub
Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX. - huggingface/diffusers
Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX. - huggingface/diffusers
MIts Lora train or checkpoint ?
Ffine tuning atm
Fafter that i plan lora
GFor multi-GPU training, does the set-up need 80gb vram TOTAL, or does EACH gpu need 80gb vram?
Ffor fine tuning
Feach gpu 80 gb
Ffor lora not necessary 48 gb gpus works great
GGottcha, thank you!
GOut of interest, what causes the VRAM per GPU requirements to jump up so much? Just curious on what's going on in the background processes that requires VRAM requirement to go from 24gb VRAM per GPU from single training to 80gb VRAM per GPU for muli-traning
Fextremely good question
Fi asked this to kohya
Fhe was also not sure
THow does multy GPU trainign work anyways?
Each GPU has a copy of a trained model and perform traning steps independantly, so how in the end we are not gettign two separate models?
Each GPU has a copy of a trained model and perform traning steps independantly, so how in the end we are not gettign two separate models?
Tthey cannot possibly synchronize model state after each step, that woudl take ages (minutes)
TAnd if the models are just merged as last step - would that mean the final model can have questionable quality (missed local minimas and such)?
Fwith diffuser models
Feach models loaded fully into vram
Flike flux sd etc
Fso we have exact replicate
Tyeah, but how the state of each model loaded into GPU sync up?
TSo the training result in single model, not multiple models
Fthey are snyched at steps
Fso it is being increased batch size
Nlong time no see. I had trained few flux loras earlier, and had to reinstall my windows recently. After that I had to reinstall kohya, and now can't train anymore. First it didn't create venv (idk, maybe it's because latest installer or something else). I've installed kohya from original repo, and it started to work. But now I have another problem. Training speed reduced. Much. ~500s/it. I guess it's because it's using ram or something. Earlier I noticed it's caching t5 and clip-l to ram (to free vram), now there is no such notice. Any suggestions?
Ngpu 4060ti 16gb, ram 64 gb
N
NI'm using the same configs I've used earlier
Nit's gpu fallback turned on, because when I'm turning it off, I'm getting out of memory error
Fwhat is your gpu and which config you are using?
Fgive me exact name pls
Ngpu 4060ti 16gb, ram 64 gb
Fok use this config 12GB_GPU_11100MB_9.5_second_it_Tier_1.json
Falso install latest nvidia but make a clean installation so all configs reset
Nnvidia driver?
Nit's dreambooth training or lora tab?
Fthis is dreambooth
Fyes nvidia driver
