Text-to-Image
Diffusers
Safetensors
English
StableDiffusionXLPipeline
stable-diffusion
stable-diffusion-xl
art
Not-For-All-Audiences
Instructions to use Runware/NoobAI-XL-VPred-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/NoobAI-XL-VPred-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/NoobAI-XL-VPred-1.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| 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-0.75 | |
| 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 1.0</strong></h1> | |
| # Repository information from Runware | |
| This model repository is uploaded with a fixed scheduler config so that inference can be seamlessly executed without special arguments. | |
| NoobAI's v_prediction model is a separate model from [Terminus XL](https://huggingface.co/collections/bghira/terminus-xl-65451893a156b3b1d1456514), another recommended model series to try if you like Illustrious and NoobAI. | |
| # 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 | |
| Hey everyone! Don’t keep the cool stuff to yourself! 🚀 | |
| If you find new tricks, wild art combos, magic prompts, or train fun LoRAs, share them openly! | |
| Post in DC/TG/X/group chats—let’s all grow together. | |
| No more secret models/prompts like the old days. | |
| Open sharing = more fun for all! 💡✨ | |
| PS: We're not trying to lock things down! Back in the 1.5/n3 days, tons of secret models/prompts popped up (ugh, messy vibes). | |
| Let’s break that cycle! Sharing = faster progress, wilder ideas, and way more hype. | |
| No gatekeeping—post your 'secret sauce' in public spaces. Everyone wins! | |
| 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 | |
| - David | |
| - **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) |