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metadata
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
  - anime
pipeline_tag: text-to-image

Hikari Noob v-pred 0.6

image/jpeg

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.
  • This model does not include any base model other than NoobAI (ν-prediction 0.5), 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
  • 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。
  • このモデルはNoobAI(ν-prediction 0.5)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 v0.6

  • v0.5 was too flat, so we improved the quality of detail rendering and made outline thinner!
  • Improved the quality of the landscapes just a little bit
  • Reduced skin color overshoot?
  • v0.5は絵柄が平坦すぎ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
  • 肌の色のオーバーシュート(白飛び)を軽減?

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: 8-24

Sampler: DPM++ 2M(dpmpp_2m)

Scheduler: Simple

Guidance Scale: 2-7

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

Notice

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.

Do not reupload this model.