常见docker使用命令

#搭建镜像

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sudo docker build -t es_refresh:V1.20230303 .

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#启动容器

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docker run -d --name=para_classify -v /etc/localtime:/etc/localtime -v /data/chenhw/multi_label_classification:/edb2vec -p 8066:8066 --gpus ‘“device=0”’ --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 edb_retrieval:V1
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#–net=host
#输出docker

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sudo docker save minutes_gen:V1.20230317 > minutes_gen.tar

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#查看镜像和容器

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sudo docker images

sudo docker ps

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#进入docker容器

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sudo docker exec -it 12e39d7323e2 /bin/bash

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#查看docker日志

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sudo docker logs --tail=1000 12e39d7323e2

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#导入镜像

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docker load -i qa-docker.tar

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#测试
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curl --location ‘http://0.0.0.0:18001/v1/chat/completions’
–header ‘Content-Type: application/json’
–data ‘{
“model”:“llama”,
“messages”: [
{
“role”: “user”,
“content”: “你是由谁训练的”
}
],
“temperature”:0.7,
“stream”: false
}’

“”"

“”"
curl --location ‘http://127.0.0.1:18001/v1/chat/completions’
–header ‘Content-Type: application/json’
–data ‘{
“model”:“gildata-llama2-13b”,
“messages”: [
{
“role”: “user”,
“content”: “你是由谁训练的”
}
],
“temperature”:0.7,
“stream”: false
}’

“”"

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curl --location ‘http://0.0.0.0:8001/v1/chat/completions’ --header ‘Content-Type: application/json’ --data ‘{
“model”:“lightgpt-70b”,
“messages”: [
{
“role”: “user”,
“content”: “你是由谁训练的”
}
],
“temperature”:0.7,
“stream”: false
}’

“”"