hopefully massed compute gets the 6000ada soon for even faster speeds
hopefully massed compute gets the 6000ada soon for even faster speeds
Fi totally agree
F
Xmade 2 loras with completely different 2 datasets, but it gets "blush" as the trigger word.
Xchanging dataset doesnt solve anything
XI dont need a trigger word, so how do I disable that?
Xdid enable shuffle caption too
Dif you already trained it, you cant change the trigger word
Fit is about your captions
Fyou need to understand how captions work
Xhmm used this to captioning, thats it. I mean I made 5loras prev, those are fine.
TIf I already have a trained model but I want to add more poses/expressions, would it be correct to take that already trained checkpoint and try only 3 or 4 photos with those expressions? What is your opinion? Because doing it again costs me more money, and this way I save time 
YPrepping a dataset right now of a human subject and most of the quality photos I have are group shots. Is there a way I can modify/psd the group shots to work for training purposes?
SCan someone please tell what base model should i use to train a face like this (half cartoon 3d render and half human like)
I was made using faceswap with an cartoon face
I was made using faceswap with an cartoon face
MA R T I U M An offshoot from my OMNIUM model, geared more towards an illustrative and painterly style, still very much infused with Omnium's DNA in...
Fi would improve dataset and do training again
Fi would avoid
Fbecause you will get mixed faces
Fi would download best models from civitiai
Fand test my prompt
Fand see which one yields best ones
Ffor generic prompts
JQuestion, I have had very good results with Onetrainer SD1.5 finetuning and LoRa extraction, now I am trying it with SDXL models, finetuning works very well,
but when I extract LoRa the similarity of the person is much weaker, this is not the case with the SD1.5 extracted LoRAs, do I just have to train longer here ?
but when I extract LoRa the similarity of the person is much weaker, this is not the case with the SD1.5 extracted LoRAs, do I just have to train longer here ?
Dbtw, how big of a quality difference are we talking about when it comes to direct lora draining vs full checkpoint training + extraction?
Jat least with my datasets i get the best results with full checkpoint training + extraction. How big the difference? i can see it, if extraction is 10 then i would give a 6 or 7
FHello! I would like to ask for some advice. How can I achieve the best settings for training SDXL Lora on OneTrainer, and what should I pay attention to? The training set consists of approximately 80-150 images of artist’s works with inconsistent aspect ratios. Thank you! 
NThe L40 & L40S are very similar to the 6000 ADA. We have a few of those available right now.
The L40 & L40S have a better server CPU and Ram as well.
The L40 & L40S have a better server CPU and Ram as well.
Mi think in terms of pricing with runpod both the l40 and 6000ada are quite cheap 79cents per hour
but on massed compute its 1.15 for the l40
but on massed compute its 1.15 for the l40
NApples to apples would be secure cloud pricing on runpod.
Fit shouldnt be case
Flast time i tested 128 rank lora was very close
Fi think a lot
Fextraction was way better for me
Fi dont have best hyper configuration for lora training
Fit requires some research
Fyou need to find best learning rate and other parameters
Fbut you can use our fine tuning parameters
Fand extract lora after training if necessary
Jthank for the info, i will try the same dataset training on different SDXL Models to see if there is a difference.
AMake the threshold lower. For me 0.0001 at most.
Ftrue make sure that diff limit low
Flike 0.000001
Jok i trained on the standard SDXL Model now, Epoch around 150 Model is really good, but the LoRA export still not close to the finetuning, i tested different threshold settings, 0.001 - 0.000001 it didn't helped. i will try later different ranks (128), do i need to change both rank and alpha to the same value?
Mare you training the text encoder as well? --train_text_encoder --learning_rate_te2 0 ??
Fi think give it a try
Fi cant test right now but i plan research and a video for this
Jonly Text Encoder 1
Mtry an older version of kohya
Mlike 22.6.2
Juh ok, i first need to learn how to rollback, never tried before
Mgit checkout 5d77bf409ff6a238aa2da94cf7910f97b8f1f1e9