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零.前言
最近NovelAI模型泄露的事可谓是闹得沸沸扬扬，一眨眼我小破站的首页推荐全都是这玩意，但我逛了一圈，却没有找到一个系统的NovelAI部署以及后续使用的教程，便打算写一篇来充充博客门面。
一.准备工作
1.Python 3.x (必须)
直接去Python官网下载最新的版本3.x版本即可
别忘了把PIP源改成清华pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
2.NovelAI.leak.Part1 (novelaileak)(必须) (约52.06GiB)
该包中包含了NovelAI的生产模型(大概是10月6日的？)，必须下载
这里仅提供磁链（我自己加了好多tracker），网盘分流你可以自己找
展开/收起
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2.NovelAI.leak.Part2 (novelaileakpt2)(可选)(约124.53GiB)
该包中包含了NovelAI的一些额外模型，比较有用的是里面的GPT模型，可惜我们暂时还不会用，可选下载
这里仅提供磁链（我自己加了好多tracker），网盘分流你可以自己找
展开/收起
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3.stable-diffusion-webui (必须)
一个webui，在Github上开源
直接git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git 来安装（如果你没有Git，请访问Git官网来安装Git）
注意！ 目前stable-diffusion-webui迭代非常快，每天都会有大量更新，因此建议每天都拉取最新代码。
4.官端 (可选)
先说下结论，在经过最后的优化后，官端与webui通过DIMM采样生成的图像质量已经几乎一致，但Eula仍有差距。有人可能会问，为啥要教部署webui而不是官端呢？因为官端想要跑起来需要至少11GB+的显存，想正常运行不容易爆显存就更恐怖了，需要20GB+，这已经不属于家用游戏显卡的范畴了。
如果你还是想部署官端，可以参考这篇文章
5.一块好Nvida显卡
显存大小很重要，越大越好，但低显存也能跑，只是容易爆，反正我没测试过最低支持多少。
性能也很重要，直接关系到出图时间。
记得安好CUDA驱动
二.部署
1.配置stable-diffusion-webui环境
这里就懒得多讲了，直接用stable-diffusion-webui自带的脚本一把梭。(注意！一定要科学上网，否则你将会痛不欲生！)
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui
webui-user.bat
这会自动帮你配置好Venv环境以及依赖。
2.复制粘贴
去前面你下载的novelaileak\stableckpt中挑一个你顺眼的模型，这里推荐选择animefull-final-pruned（当然你硬盘足够大的话全复制也没关系）,然后把它的model.ckpt复制到stable-diffusion-webui\models\Stable-diffusion，并改个容易辨识的名称。
部署教程结束咯
三.使用
1.启动&各分区功能详解
直接运行webui.bat即可，正常的话它最后会输出Running on local URL: http://127.0.0.1:XXXX （如果你二-1没出问题的话） ，直接访问这个链接即可
一般来说你会看到以下界面
txt2img
根据 Prompt 和 Negative Prompt 以及相关参数来生成图像，其实就是把文字转换成图像
img2img
根据你所提供的图像和 Prompt 与 Negative Prompt 以及相关参数来生成图像，基本上是在你所提供的图像的基础上根据 Prompt 与 Negative Prompt 以及相关参数来修改，一般被用于对txt2img中生成的比较满意的图像进行细节修改
Extras
通过超分辨率算法来对图像进行放大。因为低显存显卡无法直接在txt2img中生成高分辨率图片，因此就需要用到 Extras 来进行放大
PNG Info
可以查看由 stable-diffusion-webui 所所处理过的图片所使用的参数，包括 Prompt , Negative Prompt , Steps , Sampler , CFG scale , Seed , Face restoration , Size , Model hash 等等
Checkpoint Merger
用于混合2个模型，混合后的模型会兼有2个模型的风格，至于偏向哪个模型就看你设置的混合比例了
Textual inversion
拿来训练的。一般人用不着，用得着的也不用我教
Settings
基本上没啥好调的。你可以在Settings-Stable Diffusion-Stable Diffusion checkpoint选择你想要的模型。记得点Apply settings！
最新版stable-diffusion-webui已经可以在txt2img的左上角调整模型
2.参数详解
Prompt webui会根据此参数来生成图像，会尽可能包含Prompt中描述的元素。目前仅支持英文（和极少的几个颜文字），Prompt 是决定图像质量的最重要的参数之一
附上一张群友的 (网页链接(zcyzcy88.github.io))
Negative Prompt webui会根据此参数来生成图像，会避免出现Negative Prompt中描述的元素。目前仅支持英文，Negative Prompt 同样是是决定图像质量的最重要的参数之一
下面的解释来自TG群友
Step: 迭代多少次, 取值和 sampling method 有关, DDIM 收敛较快, 见 网页链接(www.reddit.com) 我用 DDIM 取 20 够了.
Batch count/batch size: 决定生成的图片数量, 显存够就加 batch size, 不够就 batch count, 得到的图片数量是两者之积 (小显存还是只动 count 就好)
Sampling method: 我无脑 DDIM, Eula 也挺好用? (带 a 的是 ancient 的意思, step 增长出图不稳定)
Cfg scale: 符合 prompt 的程度, 值越高越会字面看待 prompt, 低则给模型较大的发挥空间, 但是实际模型表现上来看 cfg scale 低 (6-8) 饱和度低, 偏线稿, 偏杂乱, 高 (18-22) 则饱和度偏高, 偏 CG 风格.
Denoise Strength: img2img 专属参数, 从 0 到 1 取值, 值越高 AI 对原图的参考程度就越低 (同时增加迭代次数), 我个人喜欢低 cfg 高 denoise 重绘图, 高 cfg 低 denoise 改细节.
四.优化
其实这才是重头戏
1.添加vae模型
细心地你可能已经发现了，无论是novelaileak还是novelaileakpt2，它的模型目录下都有一个叫animevae.pt的文件，这就是vae模型（它应该适用于所有NovelAI泄露模型），里面包含一些NovelAI官方的调优参数，直接把它复制丢到stable-diffusion-webui\models\Stable-diffusion下，并改名成模型名称.vae.pt（假如你在二-2中将模型重命名为了NovelAI-final-pruned.ckpt，那vae模型就该叫NovelAI-final-pruned.vae.pt）
启动时你如果能看到Loading VAE weights from:XXXX就说明你vae配置成功了
2.添加config
细心地你可能同样发现了，每个单独的模型文件夹中除了model.ckpt还有一个config.yaml，你用的是哪个模型就把它对应的config.yaml丢到stable-diffusion-webui\models\Stable-diffusion下，并改名成模型名称.yaml（假如你在二-2中将模型重命名为了NovelAI-final-pruned.ckpt，那config就该叫NovelAI-final-pruned.yaml）
3.添加hypernetworks模型
直接将novelaileak\stableckpt\modules\modules下所有文件复制到stable-diffusion-webui\models\hypernetworks下，简单粗暴
你可以在Settings-Stable Diffusion-Stable Diffusion finetune hypernetwork选择你想要的hypernetwork模型
注意！ 这一参数更多的是影响图像画风而不是图像质量，每张图以及每个人(个人口味)所适用的hypernetwork模型都是不同的！
4.修改Ignore last layers of CLIP model
这是NovelAI官方搞的小动作之一，如果将该选项保持默认会和官端有很大差距。
将Settings-Stable Siffusion-Ignore last layers of CLIP model改成2即可
注意！ 该参数仅适用于NovelAI泄露模型，别的模型请调回0！
5.使用Xformers
Xformers在生成高分辨率图片时能显著的提高图像生成速度。
30/40系卡
直接用文本编辑软件打开webui-user.bat，在COMMANDLINE_ARGS=后添加--xformers即可
然后你那一行就应该长得像这样
set COMMANDLINE_ARGS=--xformers
其他卡
其他卡需要手动编译。
注意！ 根据Github上的说法，编译Xformers需要你的电脑上有Visual Studio 2022(且已安装Desktop development with C++)和CUDA工具包11.8
cd stable-diffusion-webui\repositories
git clone https://github.com/facebookresearch/xformers.git
cd xformers
git submodule update --init --recursive
stable-diffusion-webui\venv\Scripts\activate.bat
cd stable-diffusion-webui\repositories\xformers
pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
pip install -r requirements.txt
pip install wheel
set NVCC_FLAGS=-allow-unsupported-compiler
python setup.py build
python setup.py bdist_wheel
喝杯茶，大概要花30多分钟。
中途可能会报些错，但只要最后在dist目录中生成了xformers-XXXX.whl就没问题
将xformers-XXXX.whl复制到stable-diffusion-webui目录，然后
stable-diffusion-webui\venv\Scripts\activate.bat
cd stable-diffusion-webui
pip install xformers-XXXX.whl
报错？报错那就不用呗
报错可以尝试pip install -U setuptools更新setuptools
如果最后Successfully installed Xformers啥的，就说明你安装成功了。接下来我们要启用Xformers
用文本编辑软件打开webui-user.bat，在COMMANDLINE_ARGS=后添加--force-enable-xformers
然后你那一行就应该长得像这样
set COMMANDLINE_ARGS=--force-enable-xformers
运行webui，尝试出张图，如果没报错就成了
报错？报错那就把 --force-enable-xformers删了呗
五.FAQ
1.16系显卡生成黑色/绿色图
模仿四-5，在启动参数加 --precision full --no-half
2.显存不够
模仿四-5，在启动参数加 --medvram 或 --lowvram
3.目录结构
./models
├── Codeformer
├── ESRGAN
├── GFPGAN
├── hypernetworks
│ ├── aini.pt
│ ├── anime_2.pt
│ ├── anime_3.pt
│ ├── anime.pt
│ ├── furry_2.pt
│ ├── furry_3.pt
│ ├── furry_kemono.pt
│ ├── furry_protogen.pt
│ ├── furry.pt
│ ├── furry_scalie.pt
│ ├── furry_transformation.pt
│ └── pony.pt
├── LDSR
├── Stable-diffusion
│ ├── NovelAI-final-pruned.ckpt -> novelai 的 model.ckpt (pruned)
│ ├── NovelAI-final-pruned.vae.pt -> novelai 的 animevae.pt
│ └── NovelAI-final-pruned.yaml -> novelai 的 model.ckpt (pruned) 的 config.yaml
└── SwinIR
4.高分辨率下出怪图
我原本以为是低显存触发 split attention 会这样, 不过似乎不管显存高低高分辨率都容易出怪东西.
群友的修复方法 (source)
- 使用 —medvram 或者 —lowvram 参数启动webui
- 正常输入 prompt，选择较小分辨率生成图片。记住你生成图片的分辨率。生成完毕之后，复制图片的Seed。
- 重点来了！生成完毕后，先查看图片是否满意。如果效果满意，直接将图片扔进Img2img。可点击“Send to img2img”。
- 在img2img界面底部，有一 Script 选项。将 Script 选为 SD Upscale，里面的 Tile overlap 尽量调小。
- 一般地，扔进Img2img的图，会继承原txt2img的所有prompt和negative prompt。如果你发现prompt有变动，回到txt2img，复制prompt到img2img。
- 选择合适的Sampling Steps和Sampling method。
- 确认你的 Width 和 Height 与原图一致。这一步非常重要！这里的 Width 和 Height 是超分时 img2img 的图片分割大小，如果不合适会导致出现重叠问题。
- 将第 2 步复制的 Seed 填入img2img的 Seed 里。
- Generate！
或者用 highres-fix
By default, txt2img makes horrible images at very high resolutions, and this makes it possible to avoid using the small picture’s composition.
5.我还是不会啊？
NovelAI官网请，25刀解决一切问题
六.最后的碎碎念
域名买了3年。博客前前后后搭了5,6次，结果现在才写第一篇博文，我真tm丢人
其实都是群友研究出来的，我就是整理了下，群里还有更多资料→网页链接(t.me)
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150积分
分享几张我用差不多参数画的
4040404LV4
支持一下
择言AlephLV7
0vo
显卡不好的hxd可以试一试用colab线上部署novelai，不需要配置，能上网就行，b站有教程
神的righthandLV5
want to be cooler......
收藏了
SayoriLV7
These nights are never die.
貓耳大好(^・ω・^ )
原來最近很紅的機器作畫是這樣的啊
當初第一眼看到覺得有點化學醬油 化學雪糕的感覺
用現代方式(丟給程式/加各種香精)取代傳統人力(圖層著色渲染/花時間發酵)
不是說不好 但你用超便宜價格還傻傻的以為自己買的圖/醬油是傳統工法的話
就真的冤大頭了
einsflashLV4
Error code: 1
stdout: Looking in indexes: 网页链接(pypi.org), 网页链接(download.pytorch.org)
stderr: ERROR: Could not find a version that satisfies the requirement torch==1.12.1+cu113 (from versions: none)
ERROR: No matching distribution found for torch==1.12.1+cu113
咋办
是小七吖LV3
我也遇到了这个问题，我重装低版本的python解决的（https://www.python.org/downloads/release/python-3107），然后重新clone webui的那个git项目，执行项目里面的webui-user.bat安装依赖就好了
有个名字就好LV3
封面实在是绷不住了（狗头）
良师益友LV4
想问一下，有没有人知道图片模糊怎么解决？
我想保留原图的东西多一些，denoising strength 调的很低，用同一张图往下生成，背景会越来越模糊，直到最后变成和油画一样(笑哭)
鸡鸣狗盗LV4
为毛我搞出来的不是很漂亮 QAQ