kohya_SS安装说明
安装kohya_SS gui
1.安装python：https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe
安装git：https://git-scm.com/download/win
安装：Visual Studio 2015, 2017, 2019, and 2022 redistributable
网址：https://aka.ms/vs/17/release/vc_redist.x64.exe
2.管理员打开powershell,输入Set-ExecutionPolicy Unrestricted，然后回车输入Y
3.再次打开安装盘符,输入例如cd D：（可以是任何盘符，存储空间要大），切换到安装盘符
4.创建文件夹例如D:\kohya_SS,
5.输入D:\cd \kohya_SS切换到该文件夹，
6.然后复制git clone https://github.com/bmaltais/kohya_ss.git
cd kohya_ss
.\setup.bat
安装
如果国内网速限制请在C：user/xx/创建pip环境
新建pip.txt把后缀改为.in然后用记事本打开
粘贴代码：
[global]
timeout = 6000
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
trusted-host = pypi.tuna.tsinghua.edu.cn
就可以了
下面就是运行第5步的setup.bat
会出现
1. This machine
AWS (Amazon SageMaker)
点击回车
2. No distributed training
multi-CPU
multi-GPU
TPU
多张显卡就根据情况选择，没有就按下回车
3.Do you want to run your training on CPU only（你只使用GPU训练吗） (even if a GPU / Apple Silicon device is available)? [yes/NO]:no
4.Do you wish to optimize your script with torch dynamo?[yes/NO]:no
5.Do you want to use DeepSpeed? [yes/NO]: no
6.What GPU(s) (by id) should be used for training on this machine as a comma-seperated list? [all]: all
7.Please select a choice using the arrow or number keys, and selecting with enter,no
* no
fp16
bf16
fp8
cudnn安装30/40系显卡配置，https://b1.thefileditch.ch/mwxKTEtelILoIbMbruuM.zip下载放到kohya_SS文件夹下
8.然后C:\Users\Administrator\kohya_ss>
.\venv\Scripts\activate
python .\tools\cudann_1.8_install.py
粘贴代码安装这样就安装完成啦，torch2.0自带cudnn无需安装。
9.然后运行gui-user.bat就打开UI界面啦。
