---
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](https://huggingface.co/cagliostrolab/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](https://freedevproject.org/faipl-1.0-sd/)** license.