Edit model card

UrangDiffusion 1.1

sample1
sample4
sample2
sample3
sample1
sample4

UrangDiffusion 1.1 (oo-raw-ng Diffusion) is an updated version of UrangDiffusion 1.0. This version provides improvements over the last iteration and training parameter correction.

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:

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, displeasing

Default configuration:

Euler a with around 25-30 steps, CFG 5-7, and ENSD set to 31337.

Training Configurations

Pretraining:

  • Dataset size: ~35,000 images

  • GPU: 1xA100

  • Optimizer: AdaFactor

  • Unet Learning Rate: 2.5e-6

  • Text Encoder Learning Rate: 1.25e-6

  • Batch Size: 48

  • Gradient Accumulation: 1

  • Epoch: 10

Finetuning:

  • Dataset size: ~3,100 images

  • GPU: 1xA100

  • Optimizer: AdaFactor

  • Unet Learning Rate: 2e-6

  • Text Encoder Learning Rate: - (Train TE set to False)

  • Batch Size: 48

  • Gradient Accumulation: 1

  • Epoch: 10

  • Noise Offset: 0.0357

Added Series

Wuthering Waves, Zenless Zone Zero, and hololiveEN -Justice- have been added to the model.

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.

License

UrangDiffusion 1.1 falls under the Fair AI Public License 1.0-SD license.

Downloads last month
103
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Finetuned from

Spaces using kayfahaarukku/UrangDiffusion-1.1 6

Collection including kayfahaarukku/UrangDiffusion-1.1