Model Introduction

This image generation model, based on Laxhar/noobai-XL_v1.0, leverages full Danbooru and e621 datasets with native tags and natural language captioning.

Implemented as a v-prediction model (distinct from eps-prediction), it requires specific parameter configurations - detailed in following sections.

Special thanks to my teammate euge for the coding work, and we're grateful for the technical support from many helpful community members.

⚠️ IMPORTANT NOTICE ⚠️

THIS MODEL WORKS DIFFERENT FROM EPS MODELS!

PLEASE READ THE GUIDE CAREFULLY!

Model Details

• Developed by: Laxhar Lab

• Model Type: Diffusion-based text-to-image generative model

• Fine-tuned from: Laxhar/noobai-XL_v1.0

• Sponsored by from:

  Lanyun Cloud

  Civitai & Seaart

• Collaborative testing:

  LiblibAI

  Nieta

---

How to Use the Model.

Guidebook for NoobAI XL:

ENG:

https://civitai.com/articles/8962

CHS:

https://fcnk27d6mpa5.feishu.cn/wiki/S8Z4wy7fSiePNRksiBXcyrUenOh

Method I: reForge

1. (If you haven't installed reForge) Install reForge by following the instructions in the repository;

2. Launch WebUI and use the model as usual!

Method II: ComfyUI

SAMLPLE with NODES

comfy_ui_workflow_sample

Method III: WebUI

Note that dev branch is not stable and may contain bugs.

1. (If you haven't installed WebUI) Install WebUI by following the instructions in the repository. For simp

2.Switch to dev branch:

git switch dev

3. Pull latest updates:

git pull

4. Launch WebUI and use the model as usual!

Method IV: Diffusers

import torch

from diffusers import StableDiffusionXLPipeline

from diffusers import EulerDiscreteScheduler



ckpt_path = "/path/to/model.safetensors"

pipe = StableDiffusionXLPipeline.from_single_file(

    ckpt_path,

    use_safetensors=True,

    torch_dtype=torch.float16,

)

scheduler_args = {"prediction_type": "v_prediction", "rescale_betas_zero_snr": True}

pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, **scheduler_args)

pipe.enable_xformers_memory_efficient_attention()

pipe = pipe.to("cuda")



prompt = """masterpiece, best quality,artist:john_kafka,artist:nixeu,artist:quasarcake, chromatic aberration, film grain, horror \(theme\), limited palette, x-shaped pupils, high contrast, color contrast, cold colors, arlecchino \(genshin impact\), black theme,  gritty, graphite \(medium\)"""

negative_prompt = "nsfw, worst quality, old, early, low quality, lowres, signature, username, logo, bad hands, mutated hands, mammal, anthro, furry, ambiguous form, feral, semi-anthro"



image = pipe(

    prompt=prompt,

    negative_prompt=negative_prompt,

    width=832,

    height=1216,

    num_inference_steps=28,

    guidance_scale=5,

    generator=torch.Generator().manual_seed(42),

).images[0]



image.save("output.png")

Note: Please make sure Git is installed and environment is properly configured on your machine.

---

Recommended Settings

Parameters

• CFG: 4 ~ 5

• Steps: 28 ~ 35

• Sampling Method: Euler (⚠️ Other samplers will not work properly)

• Resolution: Total area around 1024x1024. Best to choose from: 768x1344, 832x1216, 896x1152, 1024x1024, 1152x896, 1216x832, 1344x768

Prompts

• Prompt Prefix:

masterpiece, best quality, newest, absurdres, highres, safe,

• Negative Prompt:

nsfw, worst quality, old, early, low quality, lowres, signature, username, logo, bad hands, mutated hands, mammal, anthro, furry, ambiguous form, feral, semi-anthro

Usage Guidelines

Caption

<1girl/1boy/1other/...>, <character>, <series>, <artists>, <special tags>, <general tags>, <other tags>

Quality Tags

For quality tags, we evaluated image popularity through the following process:

• Data normalization based on various sources and ratings.

• Application of time-based decay coefficients according to date recency.

• Ranking of images within the entire dataset based on this processing.

Our ultimate goal is to ensure that quality tags effectively track user preferences in recent years.

Percentile RangeQuality Tags> 95thmasterpiece> 85th, <= 95thbest quality> 60th, <= 85thgood quality> 30th, <= 60thnormal quality<= 30thworst quality

Aesthetic Tags

TagDescriptionvery awaTop 5% of images in terms of aesthetic score by waifu-scorerworst aestheticAll the bottom 5% of images in terms of aesthetic score by waifu-scorer and aesthetic-shadow-v2......

Date Tags

There are two types of date tags: year tags and period tags. For year tags, use year xxxx format, i.e., year 2021. For period tags, please refer to the following table:

Year RangePeriod tag2005-2010old2011-2014early2014-2017mid2018-2020recent2021-2024newest

Dataset

• The latest Danbooru images up to the training date (approximately before 2024-10-23)

• E621 images e621-2024-webp-4Mpixel dataset on Hugging Face

Communication

• QQ Groups:

  • 875042008

  • 914818692

  • 635772191

  • 870086562

• Discord: Laxhar Dream Lab SDXL NOOB

How to train a LoRA on v-pred SDXL model

A tutorial is intended for LoRA trainers based on sd-scripts.

article link: https://civitai.com/articles/8723

Utility Tool

Laxhar Lab is training a dedicated ControlNet model for NoobXL, and the models are being released progressively. So far, the normal, depth, and canny have been released.

Model link: https://civitai.com/models/929685

Model License

This model's license inherits from https://huggingface.co/OnomaAIResearch/Illustrious-xl-early-release-v0 fair-ai-public-license-1.0-sd and adds the following terms. Any use of this model and its variants is bound by this license.

I. Usage Restrictions

• Prohibited use for harmful, malicious, or illegal activities, including but not limited to harassment, threats, and spreading misinformation.

• Prohibited generation of unethical or offensive content.

• Prohibited violation of laws and regulations in the user's jurisdiction.

II. Commercial Prohibition

We prohibit any form of commercialization, including but not limited to monetization or commercial use of the model, derivative models, or model-generated products.

III. Open Source Community

To foster a thriving open-source community,users MUST comply with the following requirements:

• Open source derivative models, merged models, LoRAs, and products based on the above models.

• Share work details such as synthesis formulas, prompts, and workflows.

• Follow the fair-ai-public-license to ensure derivative works remain open source.

IV. Disclaimer

Generated models may produce unexpected or harmful outputs. Users must assume all risks and potential consequences of usage.

Participants and Contributors

Participants

• L_A_X: Civitai | Liblib.art | Huggingface

• li_li: Civitai | Huggingface

• nebulae: Civitai | Huggingface

• Chenkin: Civitai | Huggingface

• Euge: Civitai | Huggingface | Github

Contributors

• Narugo1992: Thanks to narugo1992 and the deepghs team for open-sourcing various training sets, image processing tools, and models.

• Mikubill: Thanks to Mikubill for the Naifu trainer.

• Onommai: Thanks to OnommAI for open-sourcing a powerful base model.

• V-Prediction: Thanks to the following individuals for their detailed instructions and experiments.

  • adsfssdf

  • bluvoll

  • bvhari

  • catboxanon

  • parsee-mizuhashi

  • very-aesthetic

  • momoura

  • madmanfourohfour

• Community: aria1th261, neggles, sdtana, chewing, irldoggo, reoe, kblueleaf, Yidhar, ageless, 白玲可, Creeper, KaerMorh, 吟游诗人, SeASnAkE, zwh20081, Wenaka⁧~喵, 稀里哗啦, 幸运二副, 昨日の約, 445, EBIX, Sopp, Y_X, Minthybasis, Rakosz, 孤辰NULL, 汤人烂, 沅月弯刀,David，

描述:

This week, Noob is updating an experimental branch 0.9R, attempting to achieve a certain balance between realistic and anime styles. The feel of using it may change, so friends who want to try cosplay styles can give it a try. The triggering method can use terms like "cosplay" or "cosplay photo".

During the two-month update process, there has been joy and debate, with many experts participating in the Noob project. It is the strong involvement of the open-source community that has brought this project, which many have thought about but only existed in theory before, to fruition. The fact that NoobAI has over 100,000 downloads and  Laxhar Lab touch Creators TOP1 on Civitai is a constant reminder of this, for the open-source community, our hearts are filled with gratitude.

Furthermore, the official release of NoobAI XL's V prediction version is scheduled for this month. Friends who have been waiting for the official version, your wait is almost over. After the official release, updates for the NoobAI XL series models will temporarily come to an end. We believe that when the open-source community needs us, the spirit of open source, including Laxhar Lab, will re-emerge. Let's meet again in the new world!

训练词语: