UrangDiffusion v3.0

UrangDiffusion v3.0 (oo-raw-ng Diffusion) is the first UrangDiffusion version that utilize Animagine XL 4.0 as the base.

The name “Urang” comes from Sundanese, meaning “We/Our/I.” The history behind the name is to make the model not only suitable for me but also for many people. Another reason is that I use many resources (training scripts, dataset collecting scripts, etc.) from other people. It’s unfair to claim this model as “my sole work.”

Standard Prompting Guidelines

• Prompting guide:

  

• Default negative prompt: lowres, bad anatomy, bad hands, text, error, missing finger, extra digits, fewer digits, cropped, worst quality, low quality, low score, bad score, average score, signature, watermark, username, blurry

• Default configuration: Euler a with around 25-30 steps, CFG 5-7, and ENSD set to 31337. Sweet spot is around 27 steps and CFG 6.

Training Configurations

Finetuned from: Animagine XL 4.0-Zero

Finetuning:

• Dataset size: ~1,600 images

• GPU: 1xA100 80GB

• Optimizer: AdaFactor

• Unet Learning Rate: 1.25e-6

• Text Encoder Learning Rate: N/A (Turned off)

• Batch Size: 48

• Gradient Accumulation: 1

• Warmup steps: 5%

• Min SNR: 5

• Epoch: 11

Special Thanks

• 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, and also the person behind tag ordering.

License

UrangDiffusion v1.0-v2.5 falls under the Fair AI Public License 1.0-SD license, while v3.0 falls under the CreativeML OpenRAIL++-M license.