Sugimori Ken (Pokemon Style) (Artist Style)

https://civitai.com/models/180733/sugimori-ken-pokemon-style-artist-style

Help fuel my passion! Even $1 makes a difference. ☕ https://ko-fi.com/citronlegacyPlease checkout all my Pokemon Loras: https://civitai.com/user/CitronLegacy/models?tag=pokemonCheck out all the Art styles I’ve made: https://civitai.com/user/CitronLegacy/models?tag=styleNew v3 Version! Flatter colors with a desaturated tendency. The art looks kinda retro. Its really great for mixing with other styles because it gives a strong anime base. After collecting 890 images I realized most of Sugimori's art is retro looking. A lot of the art in this data set is from 1990-2000. Sure he still makes art but most of his art is from Pokemon gen 1 - 2Shout out to Lykon. Not only has Lykon been and still is foundational in Anime AI generation but Lykon's Ken Sugimori Style Lora is one of the first Lora's I downloaded from CivitAI.Old Version detailsThis is trained on a bunch of images by Sugimori so it kind of understands various Pokemon characters.For example you can get a Marnie-lookalike with (marnie_(Pokemon):1), 1girl, short black hair, pink dress, black jacket,The goal is to create the art style not characters but this is a nice bonus. Marnie is best girl.Two versions trained on different datasets.V1 is trained on the top 50 Sugimori images from GelbooruV2 is trained on the top 50 but with the no_humans tag applied meaning there were no humans in this dataset.Suggested weight: 0.8Please support the artist by checking out their page: https://twitter.com/SUPER_32XCheck out all the Art styles I’ve made: https://civitai.com/user/CitronLegacy/models?tag=styleTraining Datav3Trained on: 890 imagesTraining Model: AnyLoRA_noVae_fp16-prunedflip_aug: FalseNum of Repeats: 2Unit is Epochs or Steps: EpochsNumber of Epochs or Steps: 10Training Batch Size: 3Total Steps: 5933Resolution: 512Network Dim: Dim 32 and Alpha 16Lora Creation Process took: 01:30:59v1 and v2V1 and V2 Trained on 50 imagesV1 and V2 Checkpoint: AnyLoraV1 and V2 Network Dim: 16V1 Training time: 28 minutesV2 Training time: 27 minutes (why? they had the same number of images and same settings? Maybe resolution played a factor?)