<h2 id="umamusume-all-in-one-lora-k6u8az97q">Umamusume All in One LoRA</h2>This is an All-in-One LoRA designed to generate a wide variety of characters from the popular game Umamusume: Pretty Derby with a single model. Without the hassle of managing individual character LoRAs, you can easily bring numerous Umamusume to life, including Stay Gold, Almond Eye, Loves Only You, and many more, with just this one file.<h3 id="notice-g7xb14i02">Notice</h3>This model is a re-upload. The previous model page was accidentally deleted during a version update process. My apologies for the inconvenience!<h3 id="features-ubarm79mh">✨ Features</h3><ul><li>Extensive Character Library: Capable of generating most of the main characters from the game with high fidelity.</li><li>Versatile Costume Support: Faithfully reproduces each character's unique racing outfits, as well as school uniforms, casual wear, and other styles.</li><li>Easy to Use: Achieve your desired images simply by inputting character names or feature tags, without the need for complex prompts.</li></ul><h3 id="character-and-prompt-information-64t29swvm">🌟 Character &amp; Prompt Information</h3>For detailed prompt information regarding the characters, costumes, and features included in this LoRA, please refer to the Hugging Face <a target="_blank" rel="ugc" href="https://huggingface.co/datasets/UmaDiffusion/ULTIMA-prompts/blob/main/README.md">link</a>. Find the precise tags for the character you wish to create and utilize them in your prompts.<h2 id="-61q7ml2no"></h2><h2 id="license-mhq8xfg6n">License</h2><ul><li>This model is released under "<a target="_blank" rel="ugc" href="https://umamusume.jp/derivativework_guidelines/">Derivative work guidelines for umamusume</a>".</li><li>And "<a target="_blank" rel="ugc" href="https://freedevproject.org/faipl-1.0-sd/">Fair-AI public license 1.0-SD</a>" License</li></ul>

UmaMusume All In One LoRA

SDXL version<ul><li>trained on <a target="_blank" rel="ugc" href="https://github.com/kohya-ss/sd-scripts">sd-scripts by kohya_ss</a> and <a target="_blank" rel="ugc" href="https://github.com/KohakuBlueleaf/LyCORIS">LyCORIS by KohakuBlueleaf</a><ul><li>Thank you all a lot!</li></ul></li><li>Base model : <a target="_blank" rel="ugc" href="https://civitai.com/models/260267?modelVersionId=297102">Animagine XL V3.0 base</a></li><li>Hardware : 8x RTX 3090</li><li>Training time : 18 hours</li><li>Dataset : ULTIMA-UAF Dataset<ul><li>knowledge cutoff: 2024-04 (uploading is soon)</li><li>With synthetic natural language caption. half-half ratio</li><li>Max Token Length : 225</li></ul></li><li>Resolution : 1024x1024 with <a target="_blank" rel="ugc" href="https://github.com/NovelAI/novelai-aspect-ratio-bucketing">aspect ratio bucketing</a></li><li>Algorithm : LoCon<ul><li>Network dropout = 0.1</li></ul></li></ul><ul><li>Optimizer : Lion8bit<ul><li>weight decay=0.1, betas=(0.9, 0.95)</li></ul></li><li>Steps : 8,230</li><li>Total Batch size : 64<ul><li>8 GPU x 4 batch size x 2 Gradient Accumulation steps</li></ul></li><li>Learning rate :<ul><li>U-Net : 8e-5</li><li>Text Encoder 1 : 4e-5</li><li>Text Encoder 2 : 4e-5</li><li>warmup to 1e-4 for 100 steps and then kept constantLR scheduler</li></ul></li><li>LR scheduler : constant with warmup.</li><li>Min SNR gamma : 5</li><li>Noise Offset : 0.0357</li></ul>

Files with SHA256: 61be5f6c97d776dc533409b68547eab5f0f217559035bdcf654fb500649f258d