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  license: creativeml-openrail-m
 
 
 
 
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  license: creativeml-openrail-m
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+ tags:
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+ - text-to-image
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+ - stable-diffusion
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+ - diffusers
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  ---
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+
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+ # AnimeBoysXL
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+
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+ **It takes substantial time and efforts to bake models. If you appreciate my models, I would be grateful if you could support me on [Ko-fi](https://ko-fi.com/koolchh) ☕.**
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+
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+ ## Features
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+
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+ - ✔️ **Good for inference**: AnimeBoysXL is a flexible model which is good at generating images of anime boys and males-only content in a wide range of styles.
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+ - ✔️ **Good for training**: AnimeBoysXL is suitable for further training, thanks to its neutral style and ability to recognize a great deal of concepts. Feel free to train your own anime boy model/LoRA from AnimeBoysXL.
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+ - ❌ AnimeBoysXL is not optimized for creating anime girls. Please consider using other models for that purpose.
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+
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+ ## Inference Guide
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+
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+ - **Prompt**: Use tag-based prompts to describe your subject.
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+ - Append `, best quality, amazing quality, best aesthetic, absurdres` to the prompt to improve image quality.
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+ - (*Optional*) Append `, year YYYY` to the prompt to shift the output toward the prevalent style of that year. `YYYY` is a 4 digit year, e.g. `, year 2023`
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+ - **Negative prompt**: Choose from one of the following two presets.
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+ 1. Heavy (*recommended*): `lowres, (bad:1.05), text, error, missing, extra, fewer, cropped, jpeg artifacts, worst quality, bad quality, watermark, bad aesthetic, unfinished, chromatic aberration, scan, scan artifacts, 1girl, breasts`
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+ 2. Light: `lowres, jpeg artifacts, worst quality, watermark, blurry, bad aesthetic, 1girl, breasts`
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+ - (*Optional*) Add `, realistic, lips, nose` to the negative prompt if you need a flat anime-like style.
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+ - **VAE**: Make sure you're using [SDXL VAE](https://huggingface.co/stabilityai/sdxl-vae/tree/main).
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+ - **Sampling method, sampling steps and CFG scale**: I find **(Euler a, 28, 5)** good. You are encouraged to experiment with other settings.
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+ - **Width and height**: **832*1216** for portrait, **1024*1024** for square, and **1216*832** for landscape.
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+
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+ ## Training Details
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+
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+ AnimeBoysXL is trained from [Stable Diffusion XL Base 1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0), on ~516k images.
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+ The following tags are attached to the training data to make it easier to steer toward either more aesthetic or more flexible results.
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+
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+ ### Quality tags
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+
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+ | tag | score |
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+ |-------------------|------------|
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+ | `best quality` | >= 150 |
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+ | `amazing quality` | [100, 150) |
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+ | `great quality` | [75, 100) |
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+ | `normal quality` | [0, 75) |
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+ | `bad quality` | (-5, 0) |
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+ | `worst quality` | <= -5 |
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+
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+ ### Aesthetic tags
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+
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+ | tag | score |
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+ |--------------------|--------------|
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+ | `best aesthetic` | >= 6.675 |
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+ | `great aesthetic` | [6.0, 6.675) |
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+ | `normal aesthetic` | [5.0, 6.0) |
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+ | `bad aesthetic` | < 5.0 |
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+
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+ ### Rating tags
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+
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+ | tag | rating |
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+ |-----------------|--------------|
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+ | (None) | general |
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+ | `slightly nsfw` | sensitive |
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+ | `fairly nsfw` | questionable |
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+ | `very nsfw` | explicit |
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+
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+ ### Year tags
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+
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+ year YYYY where YYYY is in the range of [2005, 2023].
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+
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+ ### Training configurations
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+
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+ - Hardware: 4 * Nvidia A100 80GB GPUs
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+ - Optimizer: AdaFactor
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+ - Gradient accumulation steps: 8
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+ - Batch size: 4 * 8 * 4 = 128
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+ - Learning rates:
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+ - 8e-6 for U-Net
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+ - 5.2e-6 for text encoder 1 (CLIP ViT-L)
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+ - 4.8e-6 for text encoder 2 (OpenCLIP ViT-bigG)
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+ - Learning rate schedule: constant with 250 warmup steps
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+ - Mixed precision training type: BF16
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+ - Epochs: 20