Update README.md

README.md

@@ -3,62 +3,119 @@ license: other
 license_name: fair-ai-public-license-1.0-sd
 license_link: https://freedevproject.org/faipl-1.0-sd/
 language:
-- en
+  - en
 base_model:
-- Laxhar/noobai-XL_v1.0
+  - Laxhar/noobai-XL_v1.0
 pipeline_tag: text-to-image
 tags:
-- Diffusers
-- Safetensors
+  - safetensors
+  - diffusers
+  - stable-diffusion
+  - stable-diffusion-xl
+  - art
+library_name: diffusers
 ---
 
+<h1 align="center"><strong style="font-size: 48px;">NoobAI XL V-Pred 0.5</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. 
+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. 
+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!**
 
+## **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.
 
-## stable-diffusion-webui
+## Method I: [reForge](https://github.com/Panchovix/stable-diffusion-webui-reForge/tree/dev_upstream)
+
+1. Install reForge by following the instructions in the repository;
+2. Switch to `dev_upstream_experimental` branch by running `git checkout dev_upstream_experimental`;
+3. Launch reForge WebUI;
+4. Find "_Advanced Model Sampling for Forge_" accordion at the bottom of the "_txt2img_" tab;
+5. Enable "_Enable Advanced Model Sampling_";
+6. Select "_v_prediction_" in the "_Discrete Sampling Type_" checkbox group.
+7. Generate images!
+
+## Method II: [ComfyUI](https://github.com/comfyanonymous/ComfyUI)
+
+TODO
+
+## 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) Clone the repository:
 
-1. Clone the repository
 ```bash
 git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
 ```
 
-2. Switch to dev branch
+2. Switch to `dev` branch:
+
 ```bash
 git switch dev
 ```
 
-3. Pull latest updates
+3. Pull latest updates:
+
 ```bash
 git pull
 ```
 
-4. Use normally)
-   - Follow standard procedures to launch and use the model
+## 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")
+```
+
+4. Launch WebUI and use the model as usual.
 
-**Note**: Make sure Git is installed and environment is properly configured
+**Note**: Please make sure Git is installed and environment is properly configured on your machine.
 
 ---
 
@@ -66,71 +123,89 @@ git pull
 
 ## Parameters
 
-(For vpred model, recommend using low cfg and more Steps)
 - CFG: 4 ~ 5
-- Steps: 28 ~ 35 
-- Sampling Method:Euler a
-- Resolution:aim for around 1024\*1024
+- 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:
+
+- Prompt Prefix:
+
 ```
 masterpiece, best quality, newest, absurdres, highres, safe,
 ```
+
 - Negative Prompt:
+
 ```
- nsfw,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
+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>
-  ```
+
+```
+<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.
-   
+
+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(approximately before 2024-10-23)
+| 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
+- **QQ Groups:**
 
-* **Discord:** [Laxhar Dream Lab SDXL NOOB](https://discord.com/invite/DKnFjKEEvH)
+  - 875042008
+  - 914818692
+  - 635772191
 
+- **Discord:** [Laxhar Dream Lab SDXL NOOB](https://discord.com/invite/DKnFjKEEvH)
 
 # 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.
+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
 
@@ -158,33 +233,27 @@ Generated models may produce unexpected or harmful outputs. Users must assume al
 
 ## Participants
 
-* **L_A_X:** [Civitai](https://civitai.com/user/L_A_X) | [Liblib.art](https://www.liblib.art/userpage/9e1b16538b9657f2a737e9c2c6ebfa69)
-* **li_li:** [Civitai](https://civitai.com/user/li_li)
-* **nebulae:** [Civitai](https://civitai.com/user/kitarz)
-* **Chenkin:** [Civitai](https://civitai.com/user/Chenkin)
-* **Euge:** [Civitai](https://civitai.com/user/Euge_)
-
+- **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 and the deepghs team for open-sourcing various training sets, image processing tools, and models.
-    * [GitHub](https://github.com/narugo1992)
-    * [Hugging Face](https://huggingface.co/deepghs)
-
-* **Naifu:** Training scripts
-    * [GitHub](https://github.com/Mikubill/naifu)
-
-* **Onommai:** Thanks to onommai for open-sourcing a powerful base model.
-    * [Onommai](https://onomaai.com/)
-
-* **aria1th261:** [Civitai](https://civitai.com/user/aria1th261)
-* **neggles:** [GitHub](https://github.com/neggles/neurosis)
-* **parsee-mizuhashi:** [Hugging Face](https://huggingface.co/parsee-mizuhashi)
-* **bluvoll:** [Civitai](https://civitai.com/user/bluvoll)
-* **sdtana:** [Hugging Face](https://huggingface.co/sdtana)
-* **chewing:** [Hugging Face](https://huggingface.co/chewing)
-* **irldoggo:** [GitHub](https://github.com/irldoggo)
-* **reoe:** [Hugging Face](https://huggingface.co/reoe)
-* **kblueleaf:** [Civitai](https://civitai.com/user/kblueleaf)
-* **Yidhar:** [GitHub](https://github.com/Yidhar)
-* **Others:** 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), adsfssdf, [Minthybasis](https://civitai.com/user/Minthybasis), [Rakosz](https://civitai.com/user/Rakosz)
+- **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)
+
+- **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)