
NOTE: This model was created for my own use. There is no guarantee of quality.
Hugging Face Repo(1.0.1): https://huggingface.co/RedRayz/hikari_noob_1.0.1
Fine-tuned NoobAI-XL(v-prediction) without merging another base models, and merged SPO(Step-aware Preference Optimization) LoRA
他所のベースモデルを混ぜずに調整し、SPO LoRAをマージしたNoobAI-XL(v-prediction)
NoobAI-XL(v-prediction版)に特定画風を学習させたcheckpointを複数作成しマージしたものです,絵柄はややばらつきがあり、「典型的AIイラスト」感を抑えています,
This model does not have the "AI Masterpiece" style.
Features/特徴
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Improved stability and quality. 
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Fixed a problem in which the quality of output was significantly degraded when the number of tokens exceeded 76. 
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The base style is not strong and can be restyled by prompts or LoRAs. 
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This model does not include any base model other than NoobAI (v-prediction), so it has the equivalent knowledge. You can generate characters that have appeared by August 2024. 
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True v-prediction model with ZTSNR, No epsilon models merged 
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LoRAs for NoobAI-XL(v-prediction) work fine. 
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安定性と品質を改善 
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トークン数が76を超えると出力の品質が著しく低下する問題を修正しました, 
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素の画風は強くないので、プロンプトやLoRAによる画風変更ができます, 
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このモデルはNoobAI(v-prediction)以外のベースモデルを一切含まず、それと同等の知識があります,2024年8月までに登場したキャラクターを生成できます, 
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NoobAI-XL(v-prediction)用のLoRAがしっかり効きます, 
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真のv-prediction + ZTSNRなモデルです,Epsilonモデルは一切マージしていません, 
Requirements/動作要件
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AUTOMATIC1111 WebUI on devbranch /devブランチ上のAUTOMATIC1111 WebUI
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Latest version of ComfyUI /最新版のComfyUI 
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Latest version of Forge or reForge /最新版のForgeまたはreForge 
Instruction for AUTOMATIC1111 /AUTOMATIC1111の手順
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Switch branch to dev(Run this command in the root directory of the webui:git checkout -b dev origin/devor use Github Desktop)
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Use the model as usual! 
(日本語)
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devブランチに切り替えます(次のコマンドをwebui直下で実行します: git checkout -b dev origin/devまたはGithub Desktopを使う)
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通常通りモデルを使用します, 
Recommended Prompt/推奨プロンプト
Positive: None(works good without "masterpiece, best quality")
Negative(simple): "lowres"
Negative(long): "worst quality, bad quality, lowres, photoshop \(medium\), abstract"
Anime Style
Positive: "anime screenshot, anime screencap, anime coloring"
Negative: "worst quality, oldest"
Blue Archive Style
Positive: "official art, blue archive, game cg, non-web source, newest"
Negative: "worst quality, bad quality, low quality, lowres, photoshop \(medium\), abstract, oldest"
Recommended settings/推奨設定
Steps: 12-24
Scheduler: Simple or SGM Uniform
Guidance Scale: 2-5(best value is 4)
Note: "Align Your Steps" scheduler produces a very different image from other samplers.
Recommended Samplers/推奨サンプラー
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DPM++ 2M 
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DPM++ 2M SDE 
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Euler 
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Euler a(euler_ancestral) 
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DPM++ 3M SDE 
tips: SDE samplers will reduce deformation.
Incompatible Samplers/非対応のサンプラー
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Restart(AUTOMATIC1111/Forge) 
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UniPC(very unstable, low quality) 
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LMS(low quality) 
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PLMS(low quality) 
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Heun(broken) 
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LCM(NaN error) 
other samplers are not tested.
Incompatible Schedulers/非対応のスケジューラー
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Uniform(makes artifacts like glaze or nightshade) 
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Karras(unstable) 
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Beta(makes blurry images) 
Recommended settings for Hires.fix/Hires.fixの推奨設定
Upscaler: 4x-UltraSharp(or ESRGAN-based model), Latent(nearest-exact)
Denoising strength: 0.4-0.5(0.65-0.7 for latent)
Recommended settings for DMD2 LoRA
LoRA strength: 0.4
Steps: 6-10
Sampler: Euler/Euler a
Scheduler: Simple
Guidance Scale: 1-1.5
Note: DMD2 will change the style of the model.
Training information
Please visit the Hugging Face repository
Training script
Notice/おしらせ:
This model is licensed under Fair AI Public License 1.0-SD
If you make modify this model, you must share both your changes and the original license.
You are prohibited from monetizing any close-sourced fine-tuned /merged model, which disallows the public from accessing the model's source code /weights and its usages.
このモデルはFair AI Public License 1.0-SDでライセンスされています,
このモデルを改変する場合、変更点および元のライセンスを明記する必要があります,
モデルのソースコード/ウェイトや使用法などを閲覧できないクローズソースのファインチューン/マージモデルの収益化は禁止されています,
描述:
Updated the base model to NoobAI-XL v-prediction 0.65S
训练词语:
名称: hikariNoobVPred_065s.safetensors
大小 (KB): 6775430
类型: Model
Pickle 扫描结果: Success
Pickle 扫描信息: No Pickle imports
病毒扫描结果: Success
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                
                    
                

 
                 
                 
                 
                 
                