i should test and see if SD 1.5 broken too or not :/
i should test and see if SD 1.5 broken too or not :/
DI'm training on an rtx 3090 with Gradient checkpointing off and CrossAttention sdpa at 1.52s/it
Fnice speed
Fspda speed up
Fbut i dont know how much quality loss
D1.51s/it now, still slower than previous versions with the same settings but it is faster than using Gradient checkpointing on this capture is with an older version
DI didn't know that this option can decrease quality, what about xformers, with it also can get quality loss?
DI get almost the same speeds with xformers and a little more vram usage 20gb or so
Fyes in past both degraded
Fbut it is getting better
Dok thanks!! I will check if I can see any difference
Fi will do a training with onetrainer
Flets see difference between kohya
Dthat will be an interesting test!! a good test can be also to do a run test with xformers and spda, its a little speed up but can be very significant speed up for very large datasets and very long trainings.
Fdoing a fresh install
Fof onetrainer
Fye for massive dataset
Fyou have to have xformers and batch size bigger
RHi just checking to see if this works now ? And if so, how do I do it?
DLR Scheduler sdpa never worked on kohya_ss an sdxl models, seems to be an interesting concept I read that it automatically adjusts the learning rate or something like that.
DI don't know if it was designed to work in conjunction with CrossAttention sdpa
Fi use static LR
DYes I know, I think is the best choice for a little dataset and for training just one subject, but what do you think for other cases like bigger and probably unbalanced datasets with multiple subjects? a smart lr could be nice.
NI have trained a lora model in kohya and I have obtained better likeness and consistency than with a full dreambooth model
NLora is a underrated model
Fsmart LR not working for stable diffusion 
Fthey work for LLMs
Fprobably your config was not good for dreambooth. lora is scientifically proven to be inferior
NI used your presets 
FWhy I don't research LoRA training? Because if you need LoRA, do a full DreamBooth / Fine Tuning and extract LoRA. You will get better quality. This is for…
FYouTubeSECourses
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such compute...
NI did too, I watched and trained with onetrainer
Nsuper weird
Dohh ok I didn't know, I'm not a programmer
NUse portrait photos taken with a sony camera
NI used my photography lights to take the photos and stuff
NBut it didn't give me a good enough likenss
NI'm doing a comparison, I'll send them later too see
DWith the right parameters and number of steps full checkpoint is better, but depending your dataset number of images, etc may be it needs more steps or something
NI know, I used just kind 16 portrait photos, also realistic vision model
DI'm not an expert but I'm talking from my own experience, I had very good results with lora too I'm not gonna lie but in my opinion Dr. Furkan Gözükara is right in this one
NYeah is right
NIt seems curious to me that I spent a lot of time training and spending money training full dreambooth and I got good results but with just one time that I did lora training, it gave me very good results too
DLora is faster easier and it works fine for one purpose, but if you want to train a bigger dataset or many people at the same time full training is better, I had mixed results with both methods but I kept trying with different settings trainers and trainer versions, some with good results and some disappointing ones
PHey, does anyone know how to tell when a file has successfully uploaded into JupyterLab? I've deployed a pod with comfyui and have uploaded a lora into the lora folder, however in http, the lora step has an error. Is there any way to know when the lora has fully loaded in to jupyterlab?
TIf it is in runpod below you get like a box with the progress
PThank you!
DI was training with your new parameters, 5 people different genders and ages, no regularization images, on 30 repetitions the resemblase of the people started to get good with a simple prompt and photorealistic, but I tried some other prompts with other styles some cyberpunk and some of your prompts and they started to look baked worse and worse during the training, I was using the base model, now I stopped the training and disabled the spda optimizer and I started again, lets see..... may be is that... any idea?
I used the base model to have better compatibility with loras but if the problem continues I will try with RealVis XL 4, I'm attaching some images look ok at the beginning of the training and the baked ones with 30 repetitions
I used the base model to have better compatibility with loras but if the problem continues I will try with RealVis XL 4, I'm attaching some images look ok at the beginning of the training and the baked ones with 30 repetitions
Pdoes anyone know if there's a faster way to upload loras from the pc to runpod? At the moment it's taking around 40 minutes per lora
TUpload to huggingface and download in runpod
GCan we expect detailed youtube tutorial of this like onetrainer soon?