v1.3
In order to illustrate the quality associated with the model's randomness, I standardized the seed value at '9' for all showcase images intended for sampling and proceeded with their immediate generation.
Especially with this version, due to the significant impact of negative prompts, leaving the negative prompt field empty is likely to produce the best quality.
The spec grid(438.7 MB): download
As you can see, as the number of Steps increases, it becomes available for all samplers, and the quality also improves.
Due to the effect of the LoRA I developed and merged, as described below, using sentence-form prompts rather than tag (a list of words) prompts is directly related to improving quality.
I merged 45 checkpoints and 7 LoRAs. After that, I merged AlbedoBase v0.4 and v0.3 in order, less than 0~5%, to reawaken the diluted merged models that had become outdated.
Among the 7 LoRAs, one is created by me. It involves analyzing and annotating captions for a total of 174 high-quality pictorial photos using GPT4-V. Merging this LoRA resulted in astonishingly clear images and an impressively excellent understanding of prompts.
