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--- |
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license: other |
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license_name: faipl-1.0-sd |
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license_link: https://freedevproject.org/faipl-1.0-sd/ |
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pipeline_tag: text-to-image |
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base_model: |
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- RedRayz/illumina-xl-1.1 |
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tags: |
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- stable-diffusion |
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- stable-diffusion-xl |
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--- |
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# Abydos-XL-1.1 |
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Modified Illustrious-XL-v0.1 with Blue Archive style |
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This is the next version of Abydos-XL-1.0, Slightly improved background(scenery), stability and detail rendering. |
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You can find example images on [Civitai model page](https://civitai.com/models/832248) |
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## Prompt Guidelines |
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Almost same as the base model |
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## Recommended Prompt |
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None(Works good without `masterpiece, best quality`) |
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## Recommended Negative Prompt |
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`worst quality, low quality, bad quality, lowres, jpeg artifacts, unfinished, abstract, oldest, photoshop \(medium\)` |
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To improve the quality of background, add `simple background, transparent background` to Negative Prompt. |
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## Recommended Settings |
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Steps: 14-28 |
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Sampler: DPM++ 2M(dpmpp_2m) |
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Scheduler: Simple |
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Guidance Scale: 4-9 |
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### Hires.fix |
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Upscaler: 4x-UltraSharp or Latent |
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Denoising strength: 0.5(0.6 for latent) |
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## Training information |
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Finetuned Illumina-XL-1.1 by repeating the training and merging a DoRA 6 times with sd-scripts. |
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- Network module: lycoris_kohya(algo=lora, dora_wd=True) |
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- Resolution: 1024(Bucketing enabled, min 512, max 2048) |
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- Optimizer: Lion |
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- Train U-Net only: Yes |
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- LR Scheduler: cosine with restart(warmup ratio=0.1, repeat=4-6) |
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- Learning Rate: various(min=1e-05, max=6e-05) |
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- Noise Offset: 0.04 |
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- Immiscible Noise: 2048 |
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- Batch size: 1 |
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- Gradient Accumulation steps: 1 |
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- Dim/Alpha: 16/4 |
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- Conv Dim/Alpha: 1/0.25 |
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## Dataset information |
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Dataset size: 289 |
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## Training scripts: |
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[sd-scripts](https://github.com/kohya-ss/sd-scripts) |
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## Notice |
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This model is licensed under [Fair AI Public License 1.0-SD](https://freedevproject.org/faipl-1.0-sd/) |
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If you make modify this model, you must share both your changes and the original license. |
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You are prohibited from monetizing any close-sourced fine-tuned / merged model, which disallows the public from accessing the model's source code / weights and its usages. |
