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README.md
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#
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This
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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#
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#
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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## Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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# Training Details
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## Training Data
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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## Training Procedure [optional]
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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### Preprocessing
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[More Information Needed]
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### Speeds, Sizes, Times
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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# Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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## Testing Data, Factors & Metrics
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### Testing Data
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<!-- This should link to a Data Card if possible. -->
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[More Information Needed]
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### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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## Results
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[More Information Needed]
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### Summary
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# Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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# Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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# Technical Specifications [optional]
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## Model Architecture and Objective
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[More Information Needed]
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## Compute Infrastructure
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[More Information Needed]
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### Hardware
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[More Information Needed]
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### Software
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[More Information Needed]
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# Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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# Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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# More Information [optional]
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[More Information Needed]
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# Model Card Authors [optional]
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# Model Card Contact
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[More Information Needed]
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- stable-diffusion
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- stable-diffusion-diffusers
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---
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# Gf_style2 - 介绍
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Welcome to Gf_ Style2 model - This is a Chinese gorgeous antique style model, which can also be said to be an antique game role model with a 2.5D texture. Compared with the first generation, the second generation reduces the difficulty of getting started and can generate beautiful pictures without fixed configuration. At the same time, it also improved the problem of face collapse of the previous generation.
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This is a series of models that will be updated in the future.
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--
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欢迎使用Gf_style2模型 - 这是一个中国华丽古风风格模型,也可以说是一个古风游戏角色模型,具有2.5D的质感。第二代相对与第一代减少了上手难度,不需要固定的配置也能生成好看的图片。同时也改进了上一代脸崩坏的问题。
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这是一个模型系列,会在未来不断更新模型。
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# install - 安装教程
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1. Put the XXX.safetensors model and XXX.yaml into the SD directory
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2. Remember to select any VAE file, otherwise the drawing will be gray
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--
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1. 将XXX.saftensors模型和XXX.yaml放入SD目录
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2. 请记住选择任何VAE文件,否则图形将为灰色
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# How to use - 如何使用
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简单:第二代上手更加简单,你只需要下方3个设置即可 - simple:The second generation is easier to use. You only need the following three settings:
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- The size of the picture should be at least **768**, otherwise it will collapse - 图片大小至少768,不然会崩图
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- **key word(Start):**
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```
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{best quality}, {{masterpiece}}, {highres}, {an extremely delicate and beautiful}, original, extremely detailed wallpaper,1girl
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```
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- **Negative words:**
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```
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NSFW, lowres,bad anatomy,bad hands, text, error, missing fingers,extra digit, fewer digits, cropped, worstquality, low quality, normal quality,jpegartifacts,signature, watermark, username,blurry,bad feet
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```
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高级:如果您还想使图片尽可能更好,请尝试以下配置 - senior:If you also want to make the picture as better as possible, please try the following configuration
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- Sampling steps:**30 or 50**
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- Sampler:**DPM++ SDE Karras**
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- The size of the picture should be at least **768**, otherwise it will collapse - 图片大小至少768,不然会崩图
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- If the face is deformed, try to Open **face repair**
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- **如果想元素更丰富,可以添加下方关键词 - If you want to enrich the elements, you can add the following keywords**
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```
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strapless dress,
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smile,
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china dress,dress,hair ornament, necklace, jewelry, long hair, earrings, chinese clothes,
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```
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# Examples - 例图
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(可在文件列表中找到原图,并放入WebUi查看关键词等信息) - (You can find the original image in the file list, and put WebUi to view keywords and other information)
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