
This is AIO LoRA of Uma Musumes.
All of our works is free. If you'd like to support our team, feel free to buy me a coffee. ?
One of our team member have admission into a graduate school. So, we don't have much times. Here is some plan for this
TL;DR
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SDXL-pony-uaf
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Based on PonyXL-V6, for its variant models
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Dataset: ULTIMA-uaf
 
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SDXL-animagine
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SD1.5-uaf
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Based on SD1.5 animefull, for sd1.5 variant models. e.g. Counterfeit-V3.0
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Dataset: ULTIMA-uaf
 
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Deprecated version
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SDXL-alpha
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Based on SDXL1.0, for booru-based models. e.g. AnimagineXL,
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Dataset: ULTIMA
 
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SDXL-pony
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Based on PonyXL-V6, for pony variant models
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Dataset: ULTIMA
 
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SD1.5
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Based on SD1.5 animefull, for sd1.5 variant models. e.g. Counterfeit-V3.0
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Dataset: ULTIMA
 
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PLAN
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We will refineULTIMA Datasetfor characters who have insufficient images. Done.- 
Refining done!
 
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When the main scenario ends, we will supply the costumes or characters released during the period.- 
4 months are too short. We focus on refining dataset now. Done! 
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If there is a new Stable Diffusion model like SDXL, we will make LoRA for this depending on budget.
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I wait SD-3 will be released.
 
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As we said earlier, the above plan can be changed at any time because we don't have much time. We hope this is sustainable project.
 
NOTICE
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Some SDXL model, like Kohaku-XL Epsilon, can generate various Uma Musumes!
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For now, SDXL version isunstableandalphaversion. I made this for a test. - 
This is AIO LoRA of almost characters of Uma Musume : Pretty Derby.
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131 characters in Uma Musume: Pretty Derby
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About 300+ costumes. For each character, average 2+ costumes.
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8 official clothes for all characters.
 
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You can find all possible trigger words in here.
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Depending on model, Some characters are not able to generate.
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For example, Ikuno Dictus - Counterfeit V3.0
 
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The LoRA is optimized forHires.fix. 
Settings
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Please see ABOUT THIS VERSION in right side of page ----->
 
other training settings is included in metadata of LoRA file
License
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This model is released under "Derivative work guidelines for umamusume".
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And "Fair-AI public license 1.0-SD" License
 
描述:
Put LoRA file in your stable-diffusion-webui/models/lora folder and write lora notation in prompt to applying LoRA. <lora:your_lora_name:weight>
Recommended options
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LoRA weight 0.7
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Trigger words
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[character name] \(umamusume\) or [character name]
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For example,
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manhattan cafe \(umamusume\)
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hayakawa tazuna
 
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Settings
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For Stable Diffusion V1.5
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Use a model derived from or mixed with animefull model.
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DPM++ Series(SDE Karras, 2M Karras, etc.)
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about 20 steps, CFG scale 3.5~6.5
 
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CLIP skip = 1 or 2. Use whatever you want.
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Use Hires.fix to get higher quality image
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Upscaler
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Latent, Latent (nearest-exact), Latent (bicubic antialiased) or other Latent series.
 
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Denoising strength 0.50~0.65
 
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Training Info
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trained on sd-scripts by kohya_ss and LyCORIS by KohakuBlueleaf
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Thank you all a lot!
 
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Base model : Animefull-pruned model
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Hardware : 1x A6000 GPU
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Training time : 22 hours
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Dataset : ULTIMA Dataset
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Resolution : 768x768 with aspect ratio bucketing
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Dim, Alpha : 64
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Optimizer : lion8bit
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Steps : 20,210
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Batch size : 16
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Learning rate : warmup to 1e-4 for 1,010 steps and then kept constantLR scheduler
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LR scheduler is constant_with_warmup.
 
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other training settings is included in metadata of LoRA file.
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All uploaded images are generated by Counterfeit V3.0(huggingface, civitai).
 
训练词语: PLEASE SEE DOCUMENTS
名称: UmaMusume_AIO.safetensors
大小 (KB): 153801
类型: Model
Pickle 扫描结果: Success
Pickle 扫描信息: No Pickle imports
病毒扫描结果: Success
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
                   
                
