File size: 10,959 Bytes
bbf7b99 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 |
---
license: other
license_name: fair-ai-public-license-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
language:
- en
base_model:
- Laxhar/noobai-XL-Vpred-0.65
pipeline_tag: text-to-image
tags:
- safetensors
- diffusers
- stable-diffusion
- stable-diffusion-xl
- art
- not-for-all-audiences
library_name: diffusers
---
<h1 align="center"><strong style="font-size: 48px;">NoobAI XL V-Pred 0.75</strong></h1>
# 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](https://huggingface.co/Laxhar)
- **Model Type**: Diffusion-based text-to-image generative model
- **Fine-tuned from**: Laxhar/noobai-XL_v1.0
- **Sponsored by from**: [Lanyun Cloud](https://cloud.lanyun.net)
---
# How to Use the Model.
## Method I: [reForge](https://github.com/Panchovix/stable-diffusion-webui-reForge/tree/dev_upstream)
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](https://github.com/comfyanonymous/ComfyUI)
SAMLPLE with NODES
[comfy_ui_workflow_sample](/Laxhar/noobai-XL-Vpred-0.5/blob/main/comfy_ui_workflow_sample.png)
## Method III: [WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-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:
```bash
git switch dev
```
3. Pull latest updates:
```bash
git pull
```
4. Launch WebUI and use the model as usual!
## Method IV: [Diffusers](https://huggingface.co/docs/diffusers/en/index)
```python
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 Range | Quality Tags |
| :--------------- | :------------- |
| > 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 in terms of aesthetic score by [waifu-scorer](https://huggingface.co/Eugeoter/waifu-scorer-v4-beta) |
| worst aesthetic | All the bottom 5% of images in terms of aesthetic score by [waifu-scorer](https://huggingface.co/Eugeoter/waifu-scorer-v4-beta) and [aesthetic-shadow-v2](https://huggingface.co/shadowlilac/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 Range | Period tag |
| :--------- | :--------- |
| 2005-2010 | old |
| 2011-2014 | early |
| 2014-2017 | mid |
| 2018-2020 | recent |
| 2021-2024 | newest |
## Dataset
- The latest Danbooru images up to the training date (approximately before 2024-10-23)
- E621 images [e621-2024-webp-4Mpixel](https://huggingface.co/datasets/NebulaeWis/e621-2024-webp-4Mpixel) dataset on Hugging Face
**Communication**
- **QQ Groups:**
- 875042008
- 914818692
- 635772191
- **Discord:** [Laxhar Dream Lab SDXL NOOB](https://discord.com/invite/DKnFjKEEvH)
**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](https://civitai.com/user/L_A_X) | [Liblib.art](https://www.liblib.art/userpage/9e1b16538b9657f2a737e9c2c6ebfa69) | [Huggingface](https://huggingface.co/LAXMAYDAY)
- **li_li:** [Civitai](https://civitai.com/user/li_li) | [Huggingface](https://huggingface.co/heziiiii)
- **nebulae:** [Civitai](https://civitai.com/user/kitarz) | [Huggingface](https://huggingface.co/NebulaeWis)
- **Chenkin:** [Civitai](https://civitai.com/user/Chenkin) | [Huggingface](https://huggingface.co/windsingai)
- **Euge:** [Civitai](https://civitai.com/user/Euge_) | [Huggingface](https://huggingface.co/Eugeoter) | [Github](https://github.com/Eugeoter)
## Contributors
- **Narugo1992**: Thanks to [narugo1992](https://github.com/narugo1992) and the [deepghs](https://huggingface.co/deepghs) team for open-sourcing various training sets, image processing tools, and models.
- **Mikubill**: Thanks to [Mikubill](https://github.com/Mikubill) for the [Naifu](https://github.com/Mikubill/naifu) trainer.
- **Onommai**: Thanks to [OnommAI](https://onomaai.com/) for open-sourcing a powerful base model.
- **V-Prediction**: Thanks to the following individuals for their detailed instructions and experiments.
- adsfssdf
- [bluvoll](https://civitai.com/user/bluvoll)
- [bvhari](https://github.com/bvhari)
- [catboxanon](https://github.com/catboxanon)
- [parsee-mizuhashi](https://huggingface.co/parsee-mizuhashi)
- [very-aesthetic](https://github.com/very-aesthetic)
- [momoura](https://civitai.com/user/momoura)
- madmanfourohfour
- **Community**: [aria1th261](https://civitai.com/user/aria1th261), [neggles](https://github.com/neggles/neurosis), [sdtana](https://huggingface.co/sdtana), [chewing](https://huggingface.co/chewing), [irldoggo](https://github.com/irldoggo), [reoe](https://huggingface.co/reoe), [kblueleaf](https://civitai.com/user/kblueleaf), [Yidhar](https://github.com/Yidhar), ageless, 白玲可, Creeper, KaerMorh, 吟游诗人, SeASnAkE, [zwh20081](https://civitai.com/user/zwh20081), Wenaka~喵, 稀里哗啦, 幸运二副, 昨日の約, 445, [EBIX](https://civitai.com/user/EBIX), [Sopp](https://huggingface.co/goyishsoyish), [Y_X](https://civitai.com/user/Y_X), [Minthybasis](https://civitai.com/user/Minthybasis), [Rakosz](https://civitai.com/user/Rakosz) |