Each “version” of this LoRA is actually a different LoRA with its own capabilities, but all of them are intended to improve the base Krea2 model in some way.As I already did with SDXL, I believe this is a valid approach: using LoRAs to gradually improve the base model until it eventually becomes worth merging them into an entirely new model. At this stage, and considering that Krea2 is already quite good, my main goal with these LoRAs is to address what I see as its biggest weakness: photorealism, and especially the terrible “AI face” look that, in my opinion, still affects most generated faces.The currently available LoRAs are GP (Glamour Photography) and BP (Beautiful People), each trained on a different dataset of carefully curated, high-quality photographs. Even though the training datasets focus on people (well… women, actually), their extremely high aesthetic quality makes these LoRAs useful for virtually any type of subject. The overall idea is simply to produce better-looking images.There are no strict rules for using these LoRAs, since their purpose is broad rather than specific: to make images better. You can also combine them for a stronger effect (it is actually the best option for more realistic and impactful images), or experiment with strengths slightly above 1.0.Take a look at the example images and comparison charts to get an idea of what these LoRAs can achieve.

Araminta Better Krea [Krea2]

This is a Lora trained on ~700 high quality, carefully selected photographs with high aesthetic appeal in the "Beautiful People" style: it will impact how the faces look more that the GP Lora.

Files with SHA256: 103eb6224a13697cba4af4e0dd7bc43145044880b3284cdbda4c8c9f1a411548