about biased tag
Can this model purposefully ignore or emphasize certain elements or themes through templates，
Without significantly reducing model performance or creating illusions.
By the way, the t2i model Rouweihas designed and implemented highly responsive saturation, contrast, and even gamma labels.
May I ask about the approximate size of the images labeled with these contents during training?
If you're talking about controlling attention to the content of the described image - you can guide it very flexibly using the 'tags' field. You don't necessarily need to load a full list of booru tags, just one or two words, phrases, or a standard description can be enough.
However, if the question is about controlling the output format - it's hard-coded quite firmly, so there won't be much flexibility, perhaps only within narrow limits. To get good results you need to stick to the algo from prompts.py and example scripts, otherwise (for example if you're just using it in some chat interface) outputs will be bad.
As for training set - approximately 2.5 million unique images.
ok, i get it and thank you for your answer.
byw, regarding the fine-tuning of Qwen3.5, is Torii 0.5 the final version? (Refer to the naming conventions of previous versions)