CivArchive
    Hassaku Anima by Ikena - v1 Style
    Preview 1
    Checkpoint/Model created by Ikena (please credit them and support them whenever you can): https://civitai.com/models/2641326/hassaku-anima Description by Ikena: Hassaku aims to be an anime model with a bright, distinct, slightly 2.5D anime style. Join my Discord https://discord.gg/zSR5FcYWWE for everything related to anime models and AI art. If you’d like to support my work, you can do so on SubscribeStar https://subscribestar.adult/citrus-models Every bit helps me continue making AI models and even an AI VTuber, which is currently in the works. How to Use 30-50 steps, CFG 4-6, recommended sampler er-sde. - Put @ in front of artist tags - Use lowercase for tags and spaces instead of underscores. - Recommended positive: "masterpiece, best quality, score_7,", but since masterpiece is altered, in some cases masterpiece is enough - Recommended negative: worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia," - When using a tag that is different between Danbooru and Gelbooru, prefer the Gelbooru version. Supporters Special thanks to my supporters: pttcot, SETI, Kodokuna and dataset captioners mariotheknight and tamashiicolle Recommended Resolutions for Anima Here are some resolution suggestions for Anima: 1536 × 640 1344 × 768 1216 × 832 1152 × 896 1024 × 1024 896 × 1152 832 × 1216 — most recommended 768 × 1344 640 × 1536 Larger resolutions are possible. Note: It is a Diffusion Transformer (DiT) model, it is less restrictive on sizes in compare to a Unet like Illustrious.

    Description

    Anima has a strong issue with forgetting concepts during training and I was not able to overcome that problem so far. For example, V1 forgot Naruto’s orange outfit. Because of that, I reverted the training on NTE and Pukey back and focused my efforts on making the style more consistent. The model first received pure style training, similar to version 0.1, but more refined. On top of that, a refined style LoRA was merged into the model. Both the style training and the LoRA were trained using natural language and tags, so the style also transfers when using natural language prompts. This is a strong style-focused model, so artist tags will have a weaker effect as well tags like "realistic" or "no outline".

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