docker.io/xprobe/xinference:latest-cpu linux/amd64

docker.io/xprobe/xinference:latest-cpu - 国内下载镜像源 浏览次数:29

温馨提示:此镜像为latest tag镜像，本站无法保证此版本为最新镜像

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:latest-cpu
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:latest-cpu
镜像ID sha256:03ea70fa74c3ec47406c108f98e56e82a0dc017c3fbfe303ff949bade9b1ed46
镜像TAG latest-cpu
大小 6.75GB
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 29 次
贡献者
镜像创建 2024-09-06T09:25:33.106512699Z
同步时间 2024-09-07 01:27
更新时间 2024-09-19 15:36
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 无权限下载?点我修复 

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

Containerd拉取命令 

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

Shell快速替换命令 

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

镜像历史

大小 创建时间 层信息
0.00B 2024-09-06 17:25:33 /bin/sh -c #(nop) CMD ["/bin/bash"]
0.00B 2024-09-06 17:25:33 /bin/sh -c #(nop) ENTRYPOINT []
5.23GB 2024-09-06 17:25:18 |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="-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS" pip install llama-cpp-python && cd /opt/inference && python setup.py build_web && git restore . && pip install -i "$PIP_INDEX" --no-deps "." && pip cache purge
0.00B 2024-09-06 17:15:46 /bin/sh -c #(nop) ARG PIP_INDEX=https://pypi.org/simple
0.00B 2024-09-06 17:15:46 /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
858.54MB 2024-09-06 17:15:39 /bin/sh -c apt-get -y update && apt install -y build-essential curl procps git libgl1 ffmpeg && 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 $NODE_VERSION && nvm use default && apt-get -yq clean
0.00B 2024-09-06 17:14:38 /bin/sh -c #(nop) ENV NODE_VERSION=14.21.1
0.00B 2024-09-06 17:14:38 /bin/sh -c #(nop) ENV NVM_DIR=/usr/local/nvm
129.83MB 2024-09-06 17:14:28 /bin/sh -c #(nop) COPY dir:55ed57a4372bdcfec43928cc26956dc7ab6ea18dcb7667d01d4ab6be61a0e46f in /opt/inference
310.37MB 2023-11-17 05:10:01 RUN |1 CONDA_VERSION=py311_23.10.0-1 /bin/sh -c set -x && UNAME_M="$(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
0.00B 2023-11-17 05:09:43 ARG CONDA_VERSION=py311_23.10.0-1
0.00B 2023-11-17 05:09:43 CMD ["/bin/bash"]
0.00B 2023-11-17 05:09:43 ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
145.05MB 2023-11-17 05:09:43 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
0.00B 2023-11-17 05:09:43 ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
0.00B 2023-11-17 05:09:43 LABEL maintainer=Anaconda, Inc
0.00B 2023-11-01 08:21:12 /bin/sh -c #(nop) CMD ["bash"]
80.55MB 2023-11-01 08:21:11 /bin/sh -c #(nop) ADD file:5fb15e28ab9cd52a4c1371f9273d159579710f4efb955c1e6d76c0403e36967c in /

镜像信息 

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