try to get checkpoints every 15 20 epochs
try to get checkpoints every 15 20 epochs
Ftry to reduce VRAM usage before starting training
DYou mean 1500 -2000 steps
Fit depends
Fhow many train images
Fand reg used or not
R@Dr. Furkan Gözükara I wanna create sdxl Lora based on 15 product images.
What is the best training options?
What is the best training options?
RI am using learning_rate=1e-4 and max_train_steps=500
After I train the model, it makes some bad images
After I train the model, it makes some bad images
Rit often mixing other colors even I only trained black ones
Fwhat is your gpu?
FSDXL dreambooth much better than lora
RI am using A100
MGood afternoon guys. I was trying to ally a potential AI influencer. The problem is the photos to be taken as an example. If I take them from Instagram there is the problem of privacy/copyright but above all of quality. Solutions?
MGuys, why from this: https://civitai.com/images/2411073, on my stable diffusion became this : ? Did I do something wrong?
Sdid you use the same seed? same prompt+different seed=different picture
MI copied the generation data and pasted on prompt clicking the blue arrow to import the data on sd
A
Agives me this error for some reason I dont know why
Fyou can use our dreambooth config
Fhowever for product training the dataset matters a lot
Fi would say reinstall
Fdo a fresh one
Flibrary missing
For you need to activate venv and install missing library manually
Atried manually installing bitsandbytes no luck
DI didn't run anything else, while starting the training.
I've a core i9 cpu and a 4080 (16gb vram gpu).
I think in terms of my power, this 3000 steps should take a lot less time to train??
Again, I've used regularization images and also using a concept folder as well.
The settings are below:
Train Batch Size: 1
Epoch: 1
repeats for training images: 20.
repeats for regularization images: 2.
And for the concept folder: Training steps per concept per epoch is 20.
Mixed precision: fp16
Save precision: fp16
I've a core i9 cpu and a 4080 (16gb vram gpu).
I think in terms of my power, this 3000 steps should take a lot less time to train??
Again, I've used regularization images and also using a concept folder as well.
The settings are below:
Train Batch Size: 1
Epoch: 1
repeats for training images: 20.
repeats for regularization images: 2.
And for the concept folder: Training steps per concept per epoch is 20.
Mixed precision: fp16
Save precision: fp16
Fit is using shared vram
Fyou need to use our 16gb config
Fenable xformers and gradient checkpointing
AReinstall stable diffusion? I tried activating venv and that didn't do anything
Fit is kohya
A
Frestart
Falso your antivirus could be problem
ZHello! New here. Dreambooth training question. If I'm trying to train a model on images of a woman who doesn't have a thin body type, is having regularization images of thin women influencing the training towards a thin body type? I've been banging my head on this training for 3 days now with no real success.
ADisabled the AV.
Awell this is as far as I can get it hangs here
Fhave you tried our reg images?
Fit has mixed body types
Fgood working
Zhm, I will take a look at your reg images, I'd been using Aitrepreneur's images but it looks like your dataset is much larger (5200 images vs 1000 for his)
Zalso, do you have tips for number of images vs repeats? Is there some target I'm aiming for like images*repeats=500, or something like that?
Zoh yeah these images are way more diverse. Ethnicities, ages, body shapes. I'll have a try with these. Thanks!
Fmy images are manually collected
Fi spent over 5 days
Fi suggest repeat 200
Fand save based number of steps
Fso 1 epoch
F200 repeat
Zrepeat 200 regardless of the number of images?
Fhow many train images you have?
