These loras were trained on images from Megami Magazine from late 2018 to early 2024. Anima already knows the Megami Magazine tag but it's riddled with japanese text. These loras were trained with the text manually removed. Please read the About This Version for more information.
To get the results you see in the images above, these are the settings I used.
The lora for Anima V1 was trained at 1792 resolution. So it's capable of generating around 1792x1792 or higher.(I use 1600x1984) P2 and P3 were trained at 1536 resolution, so they're capable of generating around 1536x1536. (I use 1408x1792 for most gallery images.) It can also generate small sizes just fine.
MeMaAni - Anima V1
Trained on the same data used in Preview 3.
MeMaAni - Anima Preview 3
Trained on the same data used in Preview 2 with slight changes to improve results. Most of the improvements come from the Anima P3.
MeMaAni - Anima Preview 2
Trained on the same data used in 2d Gold Fish. I guess you could call it MeMa F, but I suppose that would make it A for this model. It uses a lot of images from the A dataset so it's close enough.
Comment On Anima
The final release of Anima 1.0 is fantastic. The model has so much capability. If you haven't made the switch, now is the time. It doesn't matter if all you post is one girl, the jump in quality, prompt comprehension, 16 channel VAE, newer anime knowledge and just raw stable performance makes it the worth while model to switch to as an anime genner.
Description
This version was trained on Anima 1.0.
This is the same dataset from P3 but trained up to a resolution of 1792x1792 (around 1.7mb). That mean you could theoretically gen at 2028x2048 but I just stick to around 1600x1984. The reason I chose a higher res than before was because Anima 1.0 supports up to 1536 and my past training tests has shown me I can get away with slightly higher training numbers.
As for the results, Anima 1.0 is a ridiculous improvement in cleanliness and coherence. Granted, I've made a few setting changes on my end that has also improved my image generation.
I highly, highly recommend you use the Sampler Method: SA Solver PECE and Schedule Type: Simple with this lora. It improves the final image greatly and gives more accurate hands and feet 7/10 times.