There was a "legend" that SDXL and SD 1.5 were trained with wrong captions

So, the custom models used millions of images with long descriptions - but apparently it was not enough. Or it changed very little. Am I wrong?

1) Which SDXL models have better adherence to the prompt? (I am not interested in illustritious and pony)

2) Which SDXL models work best with lora?

3) Which models are best for training lora?

4) Do any models have special strengths? For example, Lustify is very good with erotic images and can do male anatomy. Are there any models who are exceptionally good with skin? Or any other strengths?

I usually train with the base model, but I want to test it by training with custom models

I'm not sure, but I think models that mix other models/loras don't work. It needs to be a trained model, not a mixed model.

Until today I have always trained with the base

Some custom checkpoints were created by mixing several loras and checkpoints - as far as I know, they have strange results when applying other loras

apparently it is easy to start onetrainer from a local PC

But I have no idea how to run it using jupyterlab from rented GPU with runpod

apparently the only problem with the prodigy is that it loses flexibility

But in many cases this was the only efficient way I found to train and obtain similarity. Maybe other optimizers like lion and adafactor are "better" in the sense of generating something new, because they don't learn properly.

I don't know if I'm wrong, but at least the models from a few months ago had problems when used with lora

And apparently the custom Flux models don't solve problems like plastic skin

Should I use custom models?

Or flux base + loras?

Question 1 - dreambooth vs lora, locon, loha, lokr.

Question 2 - dim and alpha.

Question 3 - learning rate and optmizers and functions (cosine, constant, cosine with restart)

I understand that it can often be difficult to say objectively which method is best.

Some methods become very similar to the data set, but they lack flexibility, which is a problem.

And this varies from model to model. Sd 1.5 and SDXL will probably never be perfect because the model has more limitations, such as small objects distorted by Vae.

https://www.justice.gov/usao-cdca/pr/santa-clarita-man-agrees-plead-guilty-hacking-disney-employees-computer-downloading

https://variety.com/2025/film/news/disney-hack-pleads-guilty-slack-1236384302/

LOS ANGELES – A Santa Clarita man has agreed to plead guilty to hacking the personal computer of an employee of The Walt Disney Company last year, obtaining login information, and using that information to illegally download confidential data from the Burbank-based mass media and entertainment conglomerate via the employee’s Slack online communications account.

Ryan Mitchell Kramer, 25, has agreed to plead guilty to an information charging him with one count of accessing a computer and obtaining information and one count of threatening to damage a protected computer.

In addition to the information, prosecutors today filed a plea agreement in which Kramer agreed to plead guilty to the two felony charges, which each carry a statutory maximum sentence of five years in federal prison.

Kramer is expected to make his initial appearance in United States District Court in downtown Los Angeles in the coming weeks.

According to his plea agreement, in early 2024, Kramer posted a computer program on various online platforms, including GitHub, that purported to be computer program that could be used to create A.I.-generated art. In fact, the program contained a malicious file that enabled Kramer to gain access to victims’ computers.

Sometime in April and May of 2024, a victim downloaded the malicious file Kramer posted online, giving Kramer access to the victim’s personal computer, including an online account where the victim stored login credentials and passwords for the victim’s personal and work accounts.

After gaining unauthorized access to the victim’s computer and online accounts, Kramer accessed a Slack online communications account that the victim used as a Disney employee, gaining access to non-public Disney Slack channels. In May 2024, Kramer downloaded approximately 1.1 terabytes of confidential data from thousands of Disney Slack channels.

In July 2024, Kramer contacted the victim via email and the online messaging platform Discord, pretending to be a member of a fake Russia-based hacktivist group called “NullBulge.” The emails and Discord message contained threats to leak the victim’s personal information and Disney’s Slack data.

On July 12, 2024, after the victim did not respond to Kramer’s threats, Kramer publicly released the stolen Disney Slack files, as well as the victim’s bank, medical, and personal information on multiple online platforms.

Kramer admitted in his plea agreement that, in addition to the victim, at least two other victims downloaded Kramer’s malicious file, and that Kramer was able to gain unauthorized access to their computers and accounts.

The FBI is investigating this matter.

I think this can increase inference speed for people with video cards that have little VRAM

managed to reduce the model to just 500 megabytes, but I lost the post

Apparently this doesn't happen with flux because the loras are always undertrained

But it happens with SDXL

I've read comments from people saying that they train a lora with SD 1.5, generate pictures and then train another one with SDXL

Or change the face or something like that

The dim/alpha can also help. apparently if the sim is too big, the blonde absorbs more unwanted data

At least in my experience locon can give better skin textures

I tested dora - the advantage is that with different subtitles it is possible to train multiple concepts, styles, people. It doesn't mix everything up. But, it seems that it doesn't train as well as normal lora (I'm really not sure, maybe my parameters are bad)

I saw dreambooth from flux and the skin textures looked very good. But it seems that it requires a lot of vram, so I never tested it

I'm too lazy to train with flux because it's slower, kohya doesn't download the models automatically, they're much bigger

I've trained many loras with SDXL but I have little experience with flux. And it's confusing for me the ideal learning rate for flux, number of steps and optimizer. I tried prodigy but bad results for flux