README.md

---
license: other
license_name: fair-ai-public-license-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
language:
- en
base_model:
- OnomaAIResearch/Illustrious-xl-early-release-v0
pipeline_tag: text-to-image
tags:
- Diffusers
- Safetensors
---

# New Image Generation Model

This is an image generation model based on training from Illustrious-xl. 

It utilizes the latest full Danbooru and e621 datasets for training, with native tags caption.

# Recommended Settings

## Parameters
- CFG: 5 ~ 6
- Steps: 25 ~ 30
- Sampling Method:Euler a
- Resolution:aim for around 1024\*1024,±15%,such as 832\*1216
## Prompts
- Prompt:
```
masterpiece, best quality, newest, absurdres, highres, safe,
```
- Negative Prompt:
```
 worst quality,old,early,low quality,quality,lowres,signature,username,bad id,bad twitter id,english commentary,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 Range | Quality Tags |
|:-----------------|:------------------|
| > 95th           | masterpiece       |
| > 85th, <= 95th  | best quality      |
| > 60th, <= 85th  | good quality      |
| > 30th, <= 60th  | normal quality    |
| <= 30th          | worst quality     |

## Date tags
| Year Range | Period |
|:-----------------|:------------------|
| 2005-2010   | old       |
| 2011-2014   | early     |
| 2014-2017   | mid       |
| 2018-2020   | recent    |
| 2021-2024   | newest    |

## Datasets
- Latest Danbooru images up to the training date(for v1.0,it mean approximately before 2024-10-23)
- E621 images [e621-2024-webp-4Mpixel](https://huggingface.co/datasets/NebulaeWis/e621-2024-webp-4Mpixel) dataset on Hugging Face

# 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

For the open source community, you need to:

- 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.