一、环境准备1、创建一台纯净的虚拟机2、安装驱动3、下载安装Anaconda

二、部署stable-diffusion-webui1、Linux 上的自动安装2、导航到您想要安装 webui 的目录并执行以下命令：3、执行webui.sh

三、安装插件1、在WebUI上安装插件2、添加inpainting模型到指定目录

四、进行文生图测试

一、环境准备

1、创建一台纯净的虚拟机

这里我创建的是一台Ubuntu22.04的虚拟机，配置如下：

<code>CPU：8核

内存：24GB

系统盘：50G（本地硬盘）

数据盘：100G（本地硬盘）

透传设备：2块 （算力GPU-GeForce RTX 4090 D）

2、安装驱动

把 install.sh 驱动脚本传到指定目录(我是安装在了/data目录下），执行以下命令进行安装：

sh install.sh

install.sh脚本如下

<code>

#!/bin/sh

# This script installs Ollama on Linux.

# It detects the current operating system architecture and installs the appropriate version of Ollama.

set -eu

status() { echo ">>> $*" >&2; }

error() { echo "ERROR $*"; exit 1; }

warning() { echo "WARNING: $*"; }

TEMP_DIR=$(mktemp -d)

cleanup() { rm -rf $TEMP_DIR; }

trap cleanup EXIT

available() { command -v $1 >/dev/null; }

require() {

local MISSING=''code>

for TOOL in $*; do

if ! available $TOOL; then

MISSING="$MISSING $TOOL"code>

fi

done

echo $MISSING

}

[ "$(uname -s)" = "Linux" ] || error 'This script is intended to run on Linux only.'

ARCH=$(uname -m)

case "$ARCH" in

x86_64) ARCH="amd64" ;;code>

aarch64|arm64) ARCH="arm64" ;;code>

*) error "Unsupported architecture: $ARCH" ;;

esac

IS_WSL2=false

KERN=$(uname -r)

case "$KERN" in

*icrosoft*WSL2 | *icrosoft*wsl2) IS_WSL2=true;;

*icrosoft) error "Microsoft WSL1 is not currently supported. Please upgrade to WSL2 with 'wsl --set-version <distro> 2'" ;;

*) ;;

esac

VER_PARAM="${OLLAMA_VERSION:+?version=$OLLAMA_VERSION}"code>

SUDO=

if [ "$(id -u)" -ne 0 ]; then

# Running as root, no need for sudo

if ! available sudo; then

error "This script requires superuser permissions. Please re-run as root."

fi

SUDO="sudo"code>

fi

NEEDS=$(require curl awk grep sed tee xargs)

if [ -n "$NEEDS" ]; then

status "ERROR: The following tools are required but missing:"

for NEED in $NEEDS; do

echo " - $NEED"

done

exit 1

fi

# Everything from this point onwards is optional.

# WSL2 only supports GPUs via nvidia passthrough

# so check for nvidia-smi to determine if GPU is available

if [ "$IS_WSL2" = true ]; then

if available nvidia-smi && [ -n "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then

status "Nvidia GPU detected."

fi

install_success

exit 0

fi

# Install GPU dependencies on Linux

if ! available lspci && ! available lshw; then

warning "Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies."

exit 0

fi

check_gpu() {

# Look for devices based on vendor ID for NVIDIA and AMD

case $1 in

lspci)

case $2 in

nvidia) available lspci && lspci -d '10de:' | grep -q 'NVIDIA' || return 1 ;;

amdgpu) available lspci && lspci -d '1002:' | grep -q 'AMD' || return 1 ;;

esac ;;

lshw)

case $2 in

nvidia) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[10DE\]' || return 1 ;;

amdgpu) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[1002\]' || return 1 ;;

esac ;;

nvidia-smi) available nvidia-smi || return 1 ;;

esac

}

if check_gpu nvidia-smi; then

status "NVIDIA GPU installed."

exit 0

fi

if ! check_gpu lspci nvidia && ! check_gpu lshw nvidia && ! check_gpu lspci amdgpu && ! check_gpu lshw amdgpu; then

install_success

warning "No NVIDIA/AMD GPU detected. Ollama will run in CPU-only mode."

exit 0

fi

if check_gpu lspci amdgpu || check_gpu lshw amdgpu; then

# Look for pre-existing ROCm v6 before downloading the dependencies

for search in "${HIP_PATH:-''}" "${ROCM_PATH:-''}" "/opt/rocm" "/usr/lib64"; do

if [ -n "${search}" ] && [ -e "${search}/libhipblas.so.2" -o -e "${search}/lib/libhipblas.so.2" ]; then

status "Compatible AMD GPU ROCm library detected at ${search}"

install_success

exit 0

fi

done

status "Downloading AMD GPU dependencies..."

$SUDO rm -rf /usr/share/ollama/lib

$SUDO chmod o+x /usr/share/ollama

$SUDO install -o ollama -g ollama -m 755 -d /usr/share/ollama/lib/rocm

curl --fail --show-error --location --progress-bar "https://ollama.com/download/ollama-linux-amd64-rocm.tgz${VER_PARAM}" \

| $SUDO tar zx --owner ollama --group ollama -C /usr/share/ollama/lib/rocm .

install_success

status "AMD GPU ready."

exit 0

fi

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-7-centos-7

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-8-rocky-8

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-9-rocky-9

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#fedora

install_cuda_driver_yum() {

status 'Installing NVIDIA repository...'

case $PACKAGE_MANAGER in

yum)

$SUDO $PACKAGE_MANAGER -y install yum-utils

$SUDO $PACKAGE_MANAGER-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo

;;

dnf)

$SUDO $PACKAGE_MANAGER config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo

;;

esac

case $1 in

rhel)

status 'Installing EPEL repository...'

# EPEL is required for third-party dependencies such as dkms and libvdpau

$SUDO $PACKAGE_MANAGER -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-$2.noarch.rpm || true

;;

esac

status 'Installing CUDA driver...'

if [ "$1" = 'centos' ] || [ "$1$2" = 'rhel7' ]; then

$SUDO $PACKAGE_MANAGER -y install nvidia-driver-latest-dkms

fi

$SUDO $PACKAGE_MANAGER -y install cuda-drivers

}

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#debian

install_cuda_driver_apt() {

status 'Installing NVIDIA repository...'

curl -fsSL -o $TEMP_DIR/cuda-keyring.deb https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-keyring_1.1-1_all.deb

case $1 in

debian)

status 'Enabling contrib sources...'

$SUDO sed 's/main/contrib/' < /etc/apt/sources.list | $SUDO tee /etc/apt/sources.list.d/contrib.list > /dev/null

if [ -f "/etc/apt/sources.list.d/debian.sources" ]; then

$SUDO sed 's/main/contrib/' < /etc/apt/sources.list.d/debian.sources | $SUDO tee /etc/apt/sources.list.d/contrib.sources > /dev/null

fi

;;

esac

status 'Installing CUDA driver...'

$SUDO dpkg -i $TEMP_DIR/cuda-keyring.deb

$SUDO apt-get update

[ -n "$SUDO" ] && SUDO_E="$SUDO -E" || SUDO_E=code>

DEBIAN_FRONTEND=noninteractive $SUDO_E apt-get -y install cuda-drivers -q

}

if [ ! -f "/etc/os-release" ]; then

error "Unknown distribution. Skipping CUDA installation."

fi

. /etc/os-release

OS_NAME=$ID

OS_VERSION=$VERSION_ID

PACKAGE_MANAGER=

for PACKAGE_MANAGER in dnf yum apt-get; do

if available $PACKAGE_MANAGER; then

break

fi

done

if [ -z "$PACKAGE_MANAGER" ]; then

error "Unknown package manager. Skipping CUDA installation."

fi

if ! check_gpu nvidia-smi || [ -z "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then

case $OS_NAME in

centos|rhel) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -d '.' -f 1) ;;

rocky) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -c1) ;;

fedora) [ $OS_VERSION -lt '37' ] && install_cuda_driver_yum $OS_NAME $OS_VERSION || install_cuda_driver_yum $OS_NAME '37';;

amzn) install_cuda_driver_yum 'fedora' '37' ;;

debian) install_cuda_driver_apt $OS_NAME $OS_VERSION ;;

ubuntu) install_cuda_driver_apt $OS_NAME $(echo $OS_VERSION | sed 's/\.//') ;;

*) exit ;;

esac

fi

if ! lsmod | grep -q nvidia || ! lsmod | grep -q nvidia_uvm; then

KERNEL_RELEASE="$(uname -r)"code>

case $OS_NAME in

rocky) $SUDO $PACKAGE_MANAGER -y install kernel-devel kernel-headers ;;

centos|rhel|amzn) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE kernel-headers-$KERNEL_RELEASE ;;

fedora) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE ;;

debian|ubuntu) $SUDO apt-get -y install linux-headers-$KERNEL_RELEASE ;;

*) exit ;;

esac

NVIDIA_CUDA_VERSION=$($SUDO dkms status | awk -F: '/added/ { print $1 }')

if [ -n "$NVIDIA_CUDA_VERSION" ]; then

$SUDO dkms install $NVIDIA_CUDA_VERSION

fi

if lsmod | grep -q nouveau; then

status 'Reboot to complete NVIDIA CUDA driver install.'

exit 0

fi

$SUDO modprobe nvidia

$SUDO modprobe nvidia_uvm

fi

# make sure the NVIDIA modules are loaded on boot with nvidia-persistenced

if command -v nvidia-persistenced > /dev/null 2>&1; then

$SUDO touch /etc/modules-load.d/nvidia.conf

MODULES="nvidia nvidia-uvm"code>

for MODULE in $MODULES; do

if ! grep -qxF "$MODULE" /etc/modules-load.d/nvidia.conf; then

echo "$MODULE" | sudo tee -a /etc/modules-load.d/nvidia.conf > /dev/null

fi

done

fi

status "NVIDIA GPU ready."

yum -y install cuda-toolkit-12-4

install_success

驱动安装完成

3、下载安装Anaconda

<code># Debian-based:

sudo apt install wget git python3 python3-venv libgl1 libglib2.0-0

如果你的系统很新，你需要安装python3.11或者python3.10。（参考git：https://github.com/AUTOMATIC1111/stable-diffusion-webui/tree/master）

这里我在标题3、下载安装Anaconda中已安装

2、导航到您想要安装 webui 的目录并执行以下命令：

wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh

或者直接将 repo 克隆到你想要的任何位置：

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui

备注：这里git有时候不好用，所以我是直接到https://github.com/AUTOMATIC1111/stable-diffusion-webui/tree/master，下载zip包到本地，再上传到虚拟机的。

3、执行webui.sh

进入到目录：/data/stable-diffusion-webui-master/

<code>root@sssss3322-1:/data# cd stable-diffusion-webui-master/

执行bash webui.sh

这里执行bash webui.sh失败了，遇到了如下问题

这里提示“This script must not be launched as root, aborting（这个脚本不能以root身份启动，否则会中止）”，所以我尝试创建了一个新用户，但是后来也执行失败了。

最后将执行命令改为bash webui.sh -f，执行过程中遇到了以下问题：

该问题解决办法：

执行以下命令：

<code>pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple/

如果出现：

执行以下命令安装

<code>apt install python3-pip

序号3安装完成后，重新执行序号1，执行完成后显示如下：

再执行bash webui.sh -f，成功运行截图实例如下：

注意：这里虽然执行成功了，服务跑起来了，但是在网页上访问的时候出现了“此地址拒绝访问”的问题

所以，最后将执行命令改为了：

<code>bash webui.sh -f --server-name=0.0.0.0

然后在新创建的同网段的windows窗口进行访问(虚拟机IP:7860)，访问成功，截图如下：

三、安装插件

备注：访问SD的WebUI发现，没有checkpoint：

1、在WebUI上安装插件

插件安装完成后，需要重启服务生效。（“Extensions” - “Installed” - “Apply and restart UI”）

2、添加inpainting模型到指定目录

参考链接：https://www.cnblogs.com/zackstang/p/17324263.html

可以将下载的Stable Diffusion模型放在目录stable-diffusion-webui/models/Stable-diffusion/ 下。

例如，假设我们要做inpaint的调整。先在huggingface下载stable-diffusion-inpainting的checkpoint：

https://huggingface.co/runwayml/stable-diffusion-inpainting

并存放在stable-diffusion-webui/models/Stable-diffusion/ 下。

而后我们在web UI 刷新checkpoint目录即可，就得到了上图所示。

四、进行文生图测试

填入提示语，进行文生图

提示语输入可参考网上，例如：提示语

解决办法：

参考连接：Stable Diffusion WebUI linux部署问题

去网址https://huggingface.co/openai/clip-vit-large-patch14/tree/main下载以下文件：

上传至虚拟机，新建目录 mkdir -p .cache/huggingface/transformers

下载后开始进行配置，这些文件（clip）是模型中encoder所需要的，我们可以从报错信息中去发现是哪里调用了这个openai/clip-vit-large-patch14，去修改这个路径配置即可。如图，我这里显示：

根据日志信息，找到对应路径，修改相应信息：

原来是：

修改：

将version=“openai/clip-vit-large-patch14”

改为：version=“/data/stable-diffusion-webui-master/.cache/huggingface/transformers”

配置修改完成后需要重启SD服务

重启后，尝试进行文生图：

细节还可以修改左下角详细参数。