kayfahaarukku
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README.md
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**The model also available at CivitAI: https://civitai.com/models/34553**
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AingDiffusion (read: Ah-eeng Diffusion) is a merge of a bunch of anime models. This model is capable of generating high-quality anime images.
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The word "aing" came from informal Sundanese; it means "I" or "My". The name represents that this model basically produces images that are relevant to my taste.
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From my research, this model is compatible with NovelAI's animevae and pastel-mix-vae. I highly recommend pastel-mix-vae because it produces more vibrant color than animevae.
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## Samples generated using the model
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**The model also available at CivitAI: https://civitai.com/models/34553**
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Recommended models: v1.0-Q(uality)F(ix) and EXP-1
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Comparison:
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![Comparison](comparison.png)
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===
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AingDiffusion (read: Ah-eeng Diffusion) is a merge of a bunch of anime models. This model is capable of generating high-quality anime images.
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The word "aing" came from informal Sundanese; it means "I" or "My". The name represents that this model basically produces images that are relevant to my taste.
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Guide to generate good images with this model
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From my research, this model is compatible with NovelAI's animevae and pastel-mix-vae. I highly recommend pastel-mix-vae because it produces more vibrant color than animevae.
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Important: Hi-res fix is a must if you want to generate high-quality and high-resolution images. For the upscaler, I highly recommend SwinIR 4x. All the samples I uploaded are using SwinIR 4x.
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I also recommend using EasyNegative for negative prompts.
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Set Clip skip to 2, ENSD (eta noise seed delta) to 31337 and eta (noise multiplier) for ancestral samplers to 0.667.
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## Samples generated using the model
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