NoobAI-XL (NAI-XL)

NoobAI XL: A text-to-image generative model based on Danbooru and e621 datasets

NoobAI XL is an image generation model based on Laxhar/noobai-XL_v1.0. It utilizes the complete Danbooru and e621 data sets for training and supports native tags and natural language descriptions. This model uses v-prediction method (different from eps-prediction) and requires specific parameter configuration (see below for details).

Thanks: I would like to thank my teammate euge for the coding work and many community members for their technical support.

IMPORTANT NOTE: This model works differently than the eps model! Please read the guide carefully!

Model details:

Developer: Laxhar Lab

Model type: Diffusion-based text-to-image generation model

Base model: Laxhar/noobai-XL_v1.0

Sponsor: Lanyun Cloud, Civitai & Seaart

Collaborative testing: LiblibAI, Nieta

How to use:

Method 1: reForge

If reForge is not installed, follow the instructions in the repository to install it; launch the WebUI and use the model as normal.

Method 2: ComfyUI

Please refer to the node example in comfyuiworkflow_sample.

Method 3: WebUI

NOTE: The dev branch may be unstable and may contain bugs.

1. If WebUI is not installed, follow the instructions in the repository to install it.

2. Switch to the dev branch.

3. Get the latest updates.

4. Start the WebUI and use the model as usual.

Method 4: Diffusers

Note: Please ensure that Git is installed and your computer environment is configured correctly.

Recommended settings:

parameter:

* CFG: 4 ~ 5

* Number of steps: 28 ~ 35

* Sampling method: Euler (other samplers may not work properly)

* Resolution: Total area is approximately 1024x1024. Best choices: 768x1344, 832x1216, 896x1152, 1024x1024, 1152x896, 1216x832, 1344x768

Prompt words: (please provide your own prompt words and negative prompt words)

User Guide:

Description: Please provide a clear description of the image.

Quality label:

To ensure that quality labels effectively track user preferences in recent years, we evaluate image popularity through the following process:

1. Standardize data based on various sources and scores.

2. Apply a time-based decay factor based on how recent the date is.

3. Rank the images in the entire dataset based on this process.

Percent Range | Quality Label

------- | --------

95th | masterpiece

85th, <= 95th | best quality

60th, <= 85th | good quality

30th, <= 60th | normal quality

<= 30th | worst quality

Aesthetic tags:

tag | description

------- | --------

very awa | Top 5% of images rated by Waifu-scorer

worst aesthetic | Images ranked in the bottom 5% by Waifu-scorer and aesthetic-shadow-v2

Date label:

Date labels are divided into year labels and period labels. The year label uses the year xxxx format, such as year 2021. Please refer to the table below for period labels:

year range | period label

------- | --------

2005-2010 | old

2011-2014 | early

2014-2017 | mid

2018-2020 | recent

2021-2024 | newest

Dataset:

Danbooru: Latest images as of training date (approximately before October 23, 2024).

e621: e621-2024-webp-4Mpixel dataset on Hugging Face.

Contact information:

QQ group: 875042008, 914818692, 635772191, 870086562

Discord: Laxhar Dream Lab SDXL NOOB

How to train LoRA:

For a tutorial on training LoRA based on sd-scripts, please visit: https://civitai.com/articles/8723

Practical tools:

Laxhar Lab is training a dedicated NoobXL ControlNet model, which is being gradually released. Currently, normal, depth and canny models have been released. Model link: https://civitai.com/models/929685

Model license:

The license for this model is inherited from fair-ai-public-license-1.0-sd at https://huggingface.co/OnomaAIResearch/Illustrious-xl-early-release-v0, with the following terms added. Any use of this model and variations thereof is subject to this license.

I. Usage Restrictions:

Harmful, malicious or illegal activities, including but not limited to harassment, threats and dissemination of false information, are prohibited. The generation of immoral or offensive content is prohibited. Violation of the laws and regulations of the jurisdiction in which the user is located is prohibited.

II. Commercial Prohibition:

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

III. Open source community:

To promote a thriving open source community, users must adhere to the following requirements:

Open source derived models, merged models, LoRA and products based on the above models.

Share work details such as composition formulas, prompt words, and workflow.

Comply with the fair-ai-public-license to ensure derivative works remain open source.

IV. Disclaimer:

The resulting model may produce unexpected or harmful outputs. The user must bear all risks of use and potential consequences.