---
license: other
license_name: faipl-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
base_model:
- RedRayz/hikari_noob_v-pred_0.5
language:
- en
tags:
- stable-diffusion
- sdxl
---
# Hikari Noob v-pred 0.6

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.
- Works with samplers other than Euler.
- Good results with only 10 steps (12 steps or more recommended)
- 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.
- 安定性と品質を改善
- わずか10ステップでよい結果を得られます(ただし12ステップ以上を推奨)
- Zero Terminal SNRの代わりにNoise Offsetを使用することでEuler以外のサンプラーでも利用できるようにしました。
- 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。

## About v0.6
- Better detail rendering and thinner outline, because v0.5 is too flat!
- Improved the quality of the landscapes just a little bit
- のっぺりしすぎだったのでディティールを増やしてアウトラインを細くしました。
- ほんの少しだけ風景画の品質が改善

## 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, jpeg artifacts, unfinished, photoshop \(medium\), abstract` or empty(または無し)


## Recommended Settings / 推奨設定
Steps: 10-24

Sampler: DPM++ 2M(dpmpp_2m)

Scheduler: Simple

Guidance Scale: 3.5-7

### 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 Hikari Noob v-pred 0.5 and merge(see below)
*A,B: Hikari Noob v-pred 0.5 based custom checkpoint
- v0.5(NoSPO) * 0.75 + A * 0.25 = tmp1
- tmp0 * 0.75 + B * 0.25 = tmp2
- tmp2 + SPO LoRA * 1 + sdxl-flat * -0.25 + sdxl-boldline * -1 = tmp3
- Adjust tmp3(0.2,0.2,0.2,0.1,0,0,0,0) = 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.