--- 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

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**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.