AnimeBoysXL v3.0

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 ☕.

Features

• ✔️ Good for inference: AnimeBoysXL v3.0 is a flexible model which is good at generating images of anime boys and males-only content in a wide range of styles.
• ✔️ Good for training: AnimeBoysXL v3.0 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.

Inference Guide

• Prompt: Use tag-based prompts to describe your subject.
  • Tag ordering matters. It is highly recommended to structure your prompt with the following templates:

    1boy, male focus, character name, series name, anything else you'd like to describe, best quality, amazing quality, best aesthetic, absurdres
    

    2boys, male focus, multiple boys, character name(s), series name, anything else you'd like to describe, best quality, amazing quality, best aesthetic, absurdres
    

  • For more detailed documentation, you can visit my article on Ko-fi (available to supporters only).
• Negative prompt: Choose from one of the following two presets.
  1. Heavy (recommended):

  lowres, bad, text, error, missing, extra, fewer, cropped, jpeg artifacts, worst quality, bad quality, watermark, bad aesthetic, unfinished, chromatic aberration, scan, scan artifacts
  

  2. Light:

  lowres, jpeg artifacts, worst quality, watermark, blurry, bad aesthetic
  

• VAE: Make sure you're using SDXL VAE.
• Sampling method, sampling steps and CFG scale: I find (Euler a, 28, 8.5) good. You are encouraged to experiment with other settings.
• Width and height: 832*1216 for portrait, 1024*1024 for square, and 1216*832 for landscape.

🧨Diffusers Example Usage

import torch
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained("Koolchh/AnimeBoysXL-v3.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
pipe.to("cuda")

prompt = "1boy, male focus, shirt, solo, looking at viewer, smile, black hair, brown eyes, short hair, best quality, amazing quality, best aesthetic, absurdres"
negative_prompt = "lowres, bad, text, error, missing, extra, fewer, cropped, jpeg artifacts, worst quality, bad quality, watermark, bad aesthetic, unfinished, chromatic aberration, scan, scan artifacts"

image = pipe(
    prompt=prompt, 
    negative_prompt=negative_prompt, 
    width=1024,
    height=1024,
    guidance_scale=8.5,
    num_inference_steps=28
).images[0]

Training Details

AnimeBoysXL v3.0 is trained from Pony Diffusion V6 XL, on ~516k images.

The following tags are attached to the training data to make it easier to steer toward either more aesthetic or more flexible results.

Quality tags

Aesthetic tags

The aesthetic tags of AnimeBoysXL v3.0 reflect my aesthetic preference.

Rating tags

Year tags

year YYYY where YYYY is in the range of [2005, 2023].

Training configurations

• Hardware: 4 * Nvidia A100 80GB GPUs
• Optimizer: AdaFactor
• Gradient accumulation steps: 8
• Batch size: 4 * 8 * 4 = 128
• Learning rates:
  • 8e-6 for U-Net
  • 5.2e-6 for text encoder 1 (CLIP ViT-L)
  • 4.8e-6 for text encoder 2 (OpenCLIP ViT-bigG)
• Learning rate schedule: constant with 250 warmup steps
• Mixed precision training type: FP16
• Epochs: 40

Changes from v2.0

• Change the base model from Stable Diffusion XL Base 1.0 to Pony Diffusion V6 XL.
• Revamp the dataset's aesthetic tags based on the developer's preference.
• Update the criterion of quality tags.
• Use FP16 mixed-precision training.
• Train for more epochs.

Special thanks

chefFromSpace for his assistance with the showcase images.

License

Since AnimeBoysXL v3.0 is a derivative model of Pony Diffusion V6 XL by PurpleSmartAI, it has a different license from the previous versions. Please read their license before using the model.