README.md

---
license: other
license_name: faipl-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
language:
- en
tags:
- stable-diffusion
- sdxl
- anime
base_model:
- Laxhar/noobai-XL-Vpred-1.0
---

# Hikari Noob v-pred 1.0.1

Civitai model page: https://civitai.com/models/938672

Fine-tuned NoobAI-XL(ν-prediction) and merged SPO LoRA

NoobAI-XL(ν-prediction)をファインチューンし、SPOをマージしました。

## Features/特徴
- Improved stability and quality.
- Fixed a problem in which the quality of output was significantly degraded when the number of tokens exceeded 76.
- The base style is not strong and can be restyled by prompts or LoRAs.
- 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.
- 安定性と品質を改善
- 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。
- 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。
- このモデルはNoobAI(v-prediction版)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。

## About 1.0.1
- Better stability?

## Requirements / 動作要件
- AUTOMATIC1111 WebUI on `dev` branch / devブランチ上のAUTOMATIC1111 WebUI
- **Latest version** of ComfyUI / **最新版**のComfyUI
- **Latest version** of Forge or reForge / **最新版**のForgeまたはreForge

### Instruction for AUTOMATIC1111 / AUTOMATIC1111の導入手順
1. Switch branch to `dev` (Run this command in the root directory of the webui: `git checkout -b dev origin/dev` or use Github Desktop)
2. Use the model as usual!

(日本語)
1. `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)
2. 通常通りモデルを使用します。

## Prompt Guidelines / プロンプト記法
Almost same as the base model/ベースモデルとおおむね同じ

To improve the quality of background, add `simple background, transparent background` to Negative Prompt.

## Recommended Prompt / 推奨プロンプト
Positive: None/無し(Works good without `masterpiece, best quality` / `masterpiece, best quality`無しでおｋ)

Negative: `worst quality, low quality, bad quality, lowres, photoshop \(medium\), abstract` or empty


## Recommended Settings / 推奨設定
Steps: 12-24

Scheduler: Simple or SGM Uniform

Guidance Scale: 2-5(best value is 4)

### Recommended Samplers
- DPM++ 2M
- DPM++ 3M SDE
- Euler/Euler a
other samplers will not work properly.

### Hires.fix

Hires upscaler: 4x-UltraSharp or Latent(nearest-exact)

Denoising strength: 0.4-0.5(0.65-0.7 for latent)


## Merge recipe(Weighted sum)
- Stage 1: Finetune Noob v-pred 1.0 and merge(see below)
*A-K: noobai(v-pred)-based custom checkpoint
- A * 0.6 + B * 0.4 = tmp1
- tmp1 * 0.6 + C * 0.4 = tmp2
- tmp2 * 0.7 + F * 0.3 = tmp3
- tmp3 * 0.7 + E * 0.3 = tmp4
- tmp4 * 0.6 + D * 0.4 = tmp5
- tmp5 * 0.7 + G * 0.3 = tmp6
- Make H,I,J,K from tmp6
- tmp6 * 0.75 + H * 0.25 = tmp7
- tmp7 * 0.7 + I * 0.3 = tmp8
- tmp8 * 0.7 + J * 0.3 = tmp9
- tmp9 * 0.9 + K * 0.1 = tmp10
- tmp10 + SPO LoRA * 1 + sdxl-flat * -0.25 + sdxl-boldline * -1 = tmp11
- Adjust tmp11(0.2,0.2,0.2,0.05,0,0,0,0) = Result

## Training scripts:
[sd-scripts](https://github.com/kohya-ss/sd-scripts)

## Notice
This model is licensed under [Fair AI Public License 1.0-SD](https://freedevproject.org/faipl-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.