animagine3.0と3.1をマージしたanother styleです。

①

　White Unicorn_XL x (1-alpha) + FPL007(my original merge model) x alpha [Weight sum][normal]

　mbw alpha=(0.94,0.06,0.595,0.251,1.355,1.34,-0.207,-0.19,-0.41,0.568,-0.021,0.891,1.046,0.104,0.776,1.081,0.154,1.168,0.185,0.794,0)

　=Model A

②

　A x (1-alpha) + White Unicorn_XL x alpha [Weight sum][normal]

　mbw alpha=(-0.052,0.682,-0.235,0.26,1.006,0.458,0.325,0.406,-0.146,1.391,1.137,0.105,-0.222,1.045,-0.299,0.07,-0.32,0.593,0.24,1.25,0)

　=Model B

③

　B x (1-alpha) + White Unicorn_XL x alpha [Weight sum][normal]

　mbw alpha=(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.25,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0)

　=Model C

④

　C x (1-alpha-beta) + White Unicorn_XL x alpha + White Unicorn_XL_v1.1 x beta [Triple sum][tensor]

　mbw alpha=(0.514,1.257,0.493,-0.032,0.807,1.442,0.291,0.084,-0.477,-0.091,0.923,-0.074,-0.26,1.442,-0.468,1.027,0.883,-0.25,1.404,-0.203,0)

　mbw beta=(0.855,0.865,0.318,-0.357,0.559,1.3,1.252,0.484,0.261,1.074,1.178,0.525,-0.024,0.331,1.278,1.27,0.837,0.603,1.465,1.088,0)

　=Model D

⑤

　D x (1-alpha) + animagine-xl-3.1 x alpha [Weight sum][normal]

　mbw alpha=(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.423,0.0,0.524,0.421,-0.469,0.125,0.929,0.063,-0.108,1.252,0.437,0)

　=Model E

⑥

　D x (1-alpha) + animagine-xl-3.1 x alpha [Weight sum][normal]

　mbw alpha=(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.394,0.561,-0.171,-0.328,-0.22,0.508,0.541,1.421,1.093,0.446,0)

　=Model F

⑦

　F x (1-alpha) + E x alpha [Weight sum][normal]

　mbw alpha=(0.634,0.916,-0.327,1.26,0.837,0.313,1.111,1.173,0.134,0.105,1.352,0.869,0.75,0.133,0.961,-0.279,-0.479,-0.412,1.344,0.999,0)

　=Model G

⑧

　G x (1-alpha) + animagine-xl-3.0 x alpha [Weight sum][normal]

　mbw alpha=

(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-0.37,-0.155,-0.063,0.393,-0.289,-0.1,0.435,0.037,-0.339,0)

　=This model