metadata

license: other
license_name: faipl
license_link: https://freedevproject.org/faipl-1.0-sd
language:
  - en
tags:
  - text-to-image
  - stable-diffusion
  - safetensors
  - stable-diffusion-xl
base_model: cagliostrolab/animagine-xl-3.1
widget:
  - text: >-
      1girl, green hair, sweater, looking at viewer, upper body, beanie,
      outdoors, night, turtleneck, masterpiece, best quality
    parameter:
      negative_prompt: >-
        nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers,
        extra digit, fewer digits, cropped, worst quality, low quality, normal
        quality, jpeg artifacts, signature, watermark, username, blurry, artist
        name
    example_title: 1girl

UrangDiffusion 1.4

UrangDiffusion 1.4 (oo-raw-ng Diffusion) is an updated version of UrangDiffusion 1.3. This version provides refreshed dataset, better image tagging, improvements over the last iteration, training parameter correction, and better overall generation results.

Standard Prompting Guidelines

The model is finetuned from Animagine XL 3.1. However, there is a little bit changes on dataset captioning, therefore there is some different default prompt used:

Default prompt:

1girl/1boy, character name, from what series, everything else in any order, masterpiece, best quality, amazing quality, very aesthetic

Default negative prompt:

nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract],

Default configuration:

Default configuration: Euler a with around 25-30 steps, CFG 5-7, and ENSD set to 31337. Sweet spot is around 26 steps and CFG 5.

Training Configurations

Finetuned from: Animagine XL 3.1

Pretraining:

Dataset size: 34,368 images
GPU: 1xA100
Optimizer: AdaFactor
Unet Learning Rate: 3.75e-6
Text Encoder Learning Rate: 1.875e-6
Batch Size: 48
Gradient Accumulation: 1
Warmup steps: 100 steps
Min SNR Gamma: 5
Epoch: 10 (epoch 9 is used)

Finetuning:

Dataset size: 7,104 images
GPU: 1xA100
Optimizer: AdaFactor
Unet Learning Rate: 3e-6
Text Encoder Learning Rate: - (Train TE set to False)
Batch Size: 48
Gradient Accumulation: 1
Warmup steps: 5%
Min SNR Gamma: 5
Epoch: 10 (epoch 8 is used)
Noise Offset: 0.0357

Added Series

Wuthering Waves, Zenless Zone Zero, Sewayaki Kitsune no Senko-san, and hololiveEN -Justice- have been added to the model.

Special Thanks

CagliostroLab for sponsoring the model pretraining by letting me borrowed the organization’s RunPod account.
My co-workers(?) at CagliostroLab for the insights and feedback.
Nur Hikari and Vanilla Latte for quality control.
Linaqruf, my tutor and role model in AI-generated images.

License

UrangDiffusion 1.4 falls under the Fair AI Public License 1.0-SD license.