可拖拽式网站建设网站seo价格

AI Server Info

2颗（64核128线程主频2.9G,睿频3.5G)
主板：超微X12工作站主板
内存：三星RECC DDR4 32G 3200服务器校验内存 * 4
硬盘：金士顿1T NVME PCIE4.0高速固态
显卡：英伟达(NVIDIA)GeForce RTX 4090 24G * 2

1. Server info

# see if x86_64
uname -m
# see GPU
lspci | grep VGA
# output is NVIDIA GeForce RTX 4090 not AMD GPU
# 31:00.0 VGA compatible controller: NVIDIA Corporation AD102 [GeForce RTX 4090] (rev a1)
#see code name and more, Codename:    noble
cat /etc/os-release
lsb_release -a
hostnamectl

2. anaconda

wget https://repo.anaconda.com/archive/Anaconda3-2024.10-1-Linux-x86_64.sh
bash Anaconda3-2024.10-1-Linux-x86_64.sh
source ~/anaconda3/bin/activate
conda --version
conda update conda

3. ollama

see install doc

# remove first
# sudo rm -rf /usr/lib/ollama
# install auto
curl -fsSL https://ollama.com/install.sh | sh# or install manual
# using NVIDIA GeForce RTX 4090, no need install ROCm
curl -L https://ollama.com/download/ollama-linux-amd64.tgz -o ollama-linux-amd64.tgz
scp ~/Downloads/ollama-linux-amd64.tgz lwroot0@192.168.0.20:~/instal
# unzip to /usr[/lib/ollama]
sudo tar -C /usr -xzf ollama-linux-amd64.tgz# start
ollama serve
# statue
ollama -v

Adding Ollama as a startup service

Create a user and group for Ollama:

sudo useradd -r -s /bin/false -U -m -d /usr/share/ollama ollama
sudo usermod -a -G ollama $(whoami)

Create a service file in /etc/systemd/system/ollama.service:

[Unit]
Description=Ollama Service
After=network-online.target[Service]
ExecStart=/usr/bin/ollama serve
User=ollama
Group=ollama
Restart=always
RestartSec=3
Environment="PATH=$PATH"
Environment="OLLAMA_MODEL_PATH=/usr/share/ollama/.ollama/models/"
Environment="OLLAMA_HOST=0.0.0.0"[Install]
WantedBy=default.target

Then start the service:

sudo systemctl daemon-reload
sudo systemctl enable ollama

Add to user env:

vi ~/.bashrc
# add
# export OLLAMA_MODEL_PATH=/usr/share/ollama/.ollama/models/
# export OLLAMA_HOST=0.0.0.0source ~/.bashrc
echo $OLLAMA_MODEL_PATH

run AI model

You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
see models lib of ollama
model will saved in ~/.ollama/models/ or OLLAMA_MODEL_PATH

模型名称	规模	代码
deepseek-r1	14b	ollama run deepseek-r1:14b
	32b	ollama run deepseek-r1:32b
deepseek-v2	16b	ollama run deepseek-v2
qwen2.5	14b	ollama run qwen2.5:14b
phi4	14b only	ollama run phi4
glm4	9b only	ollama run glm4
llama3.1	8b	ollama run llama3.1

4. docker

see doc

# update
sudo apt update
sudo apt upgrade# Add Docker's official GPG key:
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc# Add the repository to Apt sources:
echo \"deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \$(. /etc/os-release && echo "${UBUNTU_CODENAME:-$VERSION_CODENAME}") stable" | \sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update# aliyun mirror
sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://mirrors.aliyun.com/docker-ce/linux/ubuntu/gpg | sudo tee /etc/apt/keyrings/docker.asc
sudo sh -c 'echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/docker.asc] https://mirrors.aliyun.com/docker-ce/linux/ubuntu $(lsb_release -cs) stable" > /etc/apt/sources.list.d/docker.list'
sudo apt-get update# install latest version
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin# add mirror
sudo vi /etc/docker/daemon.json
{
“registry-mirrors”:[
"https://docker.registry.cyou",
"https://docker-cf.registry.cyou",
"https://dockercf.jsdelivr.fyi",
"https://docker.jsdelivr.fyi",
"https://dockertest.jsdelivr.fyi",
"https://mirror.aliyuncs.com",
"https://dockerproxy.com",
"https://mirror.baidubce.com",
"https://docker.m.daocloud.io",
"https://docker.nju.edu.cn",
"https://docker.mirrors.sjtug.sjtu.edu.cn",
"https://docker.mirrors.ustc.edu.cn",
"https://mirror.iscas.ac.cn",
"https://docker.rainbond.cc"
]
}

MaxKB

模型概况

docker run -d --name=maxkb --restart=always -p 7861:8080 -v ~/.maxkb:/var/lib/postgresql/data -v ~/.python-packages:/opt/maxkb/app/sandbox/python-packages 1panel/maxkb# test connect to ollama
sudo docker exec -it maxkb bash
curl http://192.168.0.20:11434/
# output Ollama is runningroot@a7c89e320e86

visit: http://your_ip/7861
默认账号信息（首次登录系统强制修改）：
username: admin
password: MaxKB@123…