docker.io/xprobe/xinference:v1.4.0-cpu linux/amd64

docker.io/xprobe/xinference:v1.4.0-cpu - 国内下载镜像源 浏览次数:22
XinInference 是一个基于 Docker 的容器镜像,旨在提供一个简单、易用的机器学习推断环境。该镜像包含了 TensorFlow、PyTorch 和 scikit-learn 等常见的深度学习框架,可以用来快速 prototyping 和开发机器学习模型。
源镜像 docker.io/xprobe/xinference:v1.4.0-cpu
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu
镜像ID sha256:1449e4db01117e6e3a0a0a81408576bc123600aeab24ecac7b989aeb3d3251c2
镜像TAG v1.4.0-cpu
大小 8.82GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD /bin/bash
启动入口
工作目录
OS/平台 linux/amd64
浏览量 22 次
贡献者
镜像创建 2025-03-21T08:08:47.987443002Z
同步时间 2025-04-02 00:33
更新时间 2025-04-03 16:28
环境变量
PATH=/usr/local/nvm/versions/node/v14.21.1/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin LANG=C.UTF-8 LC_ALL=C.UTF-8 NVM_DIR=/usr/local/nvm NODE_VERSION=14.21.1
镜像标签
Anaconda, Inc: maintainer 2023-11-16T21:09:15.914Z: org.opencontainers.image.created Repository of Docker images created by Anaconda: org.opencontainers.image.description : org.opencontainers.image.licenses ebc26fe510afb782743805c76b74c0e8c558318c: org.opencontainers.image.revision https://github.com/ContinuumIO/docker-images: org.opencontainers.image.source docker-images: org.opencontainers.image.title https://github.com/ContinuumIO/docker-images: org.opencontainers.image.url 23.10.0-1: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu  docker.io/xprobe/xinference:v1.4.0-cpu

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu  docker.io/xprobe/xinference:v1.4.0-cpu

Shell快速替换命令

sed -i 's#xprobe/xinference:v1.4.0-cpu#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu  docker.io/xprobe/xinference:v1.4.0-cpu'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu  docker.io/xprobe/xinference:v1.4.0-cpu'

镜像构建历史


# 2025-03-21 16:08:47  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-03-21 16:08:47  0.00B 
/bin/sh -c #(nop)  ENTRYPOINT []
                        
# 2025-03-21 16:08:44  470.55MB 
|1 PIP_INDEX=https://pypi.org/simple /bin/sh -c /opt/conda/bin/conda create -n ffmpeg-env -c conda-forge 'ffmpeg<7' -y &&     ln -s /opt/conda/envs/ffmpeg-env/bin/ffmpeg /usr/local/bin/ffmpeg &&     ln -s /opt/conda/envs/ffmpeg-env/bin/ffprobe /usr/local/bin/ffprobe &&     /opt/conda/bin/conda clean --all -y
                        
# 2025-03-21 16:07:17  7.15GB 
|1 PIP_INDEX=https://pypi.org/simple /bin/sh -c python -m pip install --upgrade -i "$PIP_INDEX" pip &&     pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu &&     pip install -i "$PIP_INDEX" --upgrade-strategy only-if-needed -r /opt/inference/xinference/deploy/docker/requirements_cpu.txt &&     CMAKE_ARGS="-DLLAVA_BUILD=OFF" pip install llama-cpp-python &&     cd /opt/inference &&     python setup.py build_web &&     git restore . &&     pip install -i "$PIP_INDEX" --no-deps "." &&     pip install -i "$PIP_INDEX" xllamacpp &&     pip cache purge
                        
# 2025-03-21 15:56:27  0.00B 
/bin/sh -c #(nop)  ARG PIP_INDEX=https://pypi.org/simple
                        
# 2025-03-21 15:56:26  0.00B 
/bin/sh -c #(nop)  ENV PATH=/usr/local/nvm/versions/node/v14.21.1/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-03-21 15:56:22  568.66MB 
/bin/sh -c apt-get -y update   && apt install -y build-essential curl procps git libgl1   && mkdir -p $NVM_DIR   && curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash   && . $NVM_DIR/nvm.sh   && nvm install $NODE_VERSION   && nvm alias default $NODE_VERSION   && nvm use default   && apt-get -yq clean
                        
# 2025-03-21 15:55:44  0.00B 
/bin/sh -c #(nop)  ENV NODE_VERSION=14.21.1
                        
# 2025-03-21 15:55:44  0.00B 
/bin/sh -c #(nop)  ENV NVM_DIR=/usr/local/nvm
                        
# 2025-03-21 15:55:38  97.92MB 
/bin/sh -c #(nop) COPY dir:4d28d48efb587aae534e429bea49b7699d543f4aa0651cb93141b6fa6a48de21 in /opt/inference 
                        
# 2023-11-17 05:10:01  310.37MB 执行命令并创建新的镜像层
RUN |1 CONDA_VERSION=py311_23.10.0-1 /bin/sh -c set -x &&     UNAME_M="$(uname -m)" &&     if [ "${UNAME_M}" = "x86_64" ]; then         MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-${CONDA_VERSION}-Linux-x86_64.sh";         SHA256SUM="d0643508fa49105552c94a523529f4474f91730d3e0d1f168f1700c43ae67595";     elif [ "${UNAME_M}" = "s390x" ]; then         MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-${CONDA_VERSION}-Linux-s390x.sh";         SHA256SUM="ae212385c9d7f7473da7401d3f5f6cbbbc79a1fce730aa48531947e9c07e0808";     elif [ "${UNAME_M}" = "aarch64" ]; then         MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-${CONDA_VERSION}-Linux-aarch64.sh";         SHA256SUM="a60e70ad7e8ac5bb44ad876b5782d7cdc66e10e1f45291b29f4f8d37cc4aa2c8";     elif [ "${UNAME_M}" = "ppc64le" ]; then         MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-${CONDA_VERSION}-Linux-ppc64le.sh";         SHA256SUM="1a2eda0a9a52a4bd058abbe9de5bb2bc751fcd7904c4755deffdf938d6f4436e";     fi &&     wget "${MINICONDA_URL}" -O miniconda.sh -q &&     echo "${SHA256SUM} miniconda.sh" > shasum &&     if [ "${CONDA_VERSION}" != "latest" ]; then sha256sum --check --status shasum; fi &&     mkdir -p /opt &&     bash miniconda.sh -b -p /opt/conda &&     rm miniconda.sh shasum &&     ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh &&     echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc &&     echo "conda activate base" >> ~/.bashrc &&     find /opt/conda/ -follow -type f -name '*.a' -delete &&     find /opt/conda/ -follow -type f -name '*.js.map' -delete &&     /opt/conda/bin/conda clean -afy # buildkit
                        
# 2023-11-17 05:09:43  0.00B 定义构建参数
ARG CONDA_VERSION=py311_23.10.0-1
                        
# 2023-11-17 05:09:43  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2023-11-17 05:09:43  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-11-17 05:09:43  145.05MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update -q &&     apt-get install -q -y --no-install-recommends         bzip2         ca-certificates         git         libglib2.0-0         libsm6         libxext6         libxrender1         mercurial         openssh-client         procps         subversion         wget     && apt-get clean     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-17 05:09:43  0.00B 设置环境变量 LANG LC_ALL
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
                        
# 2023-11-17 05:09:43  0.00B 添加元数据标签
LABEL maintainer=Anaconda, Inc
                        
# 2023-11-01 08:21:12  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2023-11-01 08:21:11  80.55MB 
/bin/sh -c #(nop) ADD file:5fb15e28ab9cd52a4c1371f9273d159579710f4efb955c1e6d76c0403e36967c in / 
                        
                    

镜像信息

{
    "Id": "sha256:1449e4db01117e6e3a0a0a81408576bc123600aeab24ecac7b989aeb3d3251c2",
    "RepoTags": [
        "xprobe/xinference:v1.4.0-cpu",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v1.4.0-cpu"
    ],
    "RepoDigests": [
        "xprobe/xinference@sha256:3b4f3a8239deddb4413d156680f1b34e3070783426e7e3fc05e1f84722f6e448",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference@sha256:3b4f3a8239deddb4413d156680f1b34e3070783426e7e3fc05e1f84722f6e448"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2025-03-21T08:08:47.987443002Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "20.10.17",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/usr/local/nvm/versions/node/v14.21.1/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "LANG=C.UTF-8",
            "LC_ALL=C.UTF-8",
            "NVM_DIR=/usr/local/nvm",
            "NODE_VERSION=14.21.1"
        ],
        "Cmd": [
            "/bin/bash"
        ],
        "Image": "sha256:4ee2407f062e5bb5c60df5c2802953357981f55499ed701a78b05e84afab7d86",
        "Volumes": null,
        "WorkingDir": "",
        "Entrypoint": null,
        "OnBuild": null,
        "Labels": {
            "maintainer": "Anaconda, Inc",
            "org.opencontainers.image.created": "2023-11-16T21:09:15.914Z",
            "org.opencontainers.image.description": "Repository of Docker images created by Anaconda",
            "org.opencontainers.image.licenses": "",
            "org.opencontainers.image.revision": "ebc26fe510afb782743805c76b74c0e8c558318c",
            "org.opencontainers.image.source": "https://github.com/ContinuumIO/docker-images",
            "org.opencontainers.image.title": "docker-images",
            "org.opencontainers.image.url": "https://github.com/ContinuumIO/docker-images",
            "org.opencontainers.image.version": "23.10.0-1"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 8823538476,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/803edd92ce9403c16477057af569a78b2d5260fbaa5928e0e525b0d2b77643aa/diff:/var/lib/docker/overlay2/def2015d40c8a3a292b2e20fe21c4d11ab109ac0439017746952264a7cff5488/diff:/var/lib/docker/overlay2/ded9f3b8686b6a800bbc9ea8d7cc6931cdab25ebd1d700c074e378b17d196be5/diff:/var/lib/docker/overlay2/a87a3d3c0b9290a8363bb8afe70718e034a1f357e81faf4aa6d34477365f0e8b/diff:/var/lib/docker/overlay2/8e8181d9a68f68c5bf5d0c40d2ecf4498fd5c598271da8669b53ed262db0b543/diff:/var/lib/docker/overlay2/1eb9be2eb3653df6ac20e93d0db6a8c53abde1dfe4776b7d05dd65e5f8f0a0aa/diff",
            "MergedDir": "/var/lib/docker/overlay2/ab65f20e4993a7d47b0c397439e64b763e7d0585e5910dc907c4777d3afd82c7/merged",
            "UpperDir": "/var/lib/docker/overlay2/ab65f20e4993a7d47b0c397439e64b763e7d0585e5910dc907c4777d3afd82c7/diff",
            "WorkDir": "/var/lib/docker/overlay2/ab65f20e4993a7d47b0c397439e64b763e7d0585e5910dc907c4777d3afd82c7/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:74c0af6e02274b54b88f851843ae69880a234694dede8ff9fb93bfa076af45ed",
            "sha256:2274c4bfd58ef49f18adf395a0382997bf49db151c10eeb4e231dafcaac465a4",
            "sha256:d917f59154bf3be5c8da57f7a5f81ec6c0d001037cafd5c00bf853433e691c30",
            "sha256:84de032710c0db72c44786fa5d69cf3fcd43a88565520dd33a571a1af0e74a98",
            "sha256:1e381151e79b0c26773033f6a2646335a2aa5b0c1ff0cebdc004a778fe9f4c03",
            "sha256:659575a2f20f08f0b24c889f96cf47ea385947919365ba0ab4a672ab1f35932d",
            "sha256:7da9023710132cffd4c9b458c469562da552b2285b18ba9194f432d7e196741c"
        ]
    },
    "Metadata": {
        "LastTagTime": "2025-04-02T00:27:16.348298298+08:00"
    }
}

更多版本

docker.io/xprobe/xinference:v0.13.3

linux/amd64 docker.io15.44GB2024-08-03 22:15
688

docker.io/xprobe/xinference:v0.14.0

linux/amd64 docker.io15.53GB2024-08-05 11:11
533

docker.io/xprobe/xinference:latest-cpu

linux/amd64 docker.io6.75GB2024-09-07 01:27
408

docker.io/xprobe/xinference:v0.12.1

linux/amd64 docker.io26.68GB2024-09-07 03:07
238

docker.io/xprobe/xinference:v0.15.0-cpu

linux/amd64 docker.io6.75GB2024-09-19 22:49
264

docker.io/xprobe/xinference:v0.12.0

linux/amd64 docker.io27.66GB2024-09-25 04:01
229

docker.io/xprobe/xinference:v0.15.2

linux/amd64 docker.io17.55GB2024-09-30 13:35
205

docker.io/xprobe/xinference:v0.15.4

linux/amd64 docker.io17.54GB2024-10-16 01:44
286

docker.io/xprobe/xinference:v0.16.3

linux/amd64 docker.io17.59GB2024-11-13 00:44
159

docker.io/xprobe/xinference:v1.0.0

linux/amd64 docker.io17.62GB2024-11-19 00:15
180

docker.io/xprobe/xinference:v1.0.1

linux/amd64 docker.io17.60GB2024-12-04 00:49
160

docker.io/xprobe/xinference:v1.1.0

linux/amd64 docker.io18.25GB2024-12-18 00:16
220

docker.io/xprobe/xinference:v1.2.0

linux/amd64 docker.io17.01GB2025-01-15 00:31
114

docker.io/xprobe/xinference:v1.2.1

linux/amd64 docker.io23.34GB2025-01-27 00:55
223

docker.io/xprobe/xinference:v1.2.2

linux/amd64 docker.io23.55GB2025-02-13 01:30
255

docker.io/xprobe/xinference:v1.3.0

linux/amd64 docker.io23.65GB2025-03-03 01:51
274

docker.io/xprobe/xinference:v1.3.1.post1

linux/amd64 docker.io25.86GB2025-03-13 01:23
129

docker.io/xprobe/xinference:v1.3.1

linux/amd64 docker.io25.83GB2025-03-19 01:04
161

docker.io/xprobe/xinference:v1.4.0

linux/amd64 docker.io26.27GB2025-03-22 01:34
228

docker.io/xprobe/xinference:v0.15.4-cpu

linux/amd64 docker.io6.78GB2025-04-01 20:33
13

docker.io/xprobe/xinference:v1.4.0-cpu

linux/amd64 docker.io8.82GB2025-04-02 00:33
21