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注意:这是一个 latest 标签镜像

latest 并不代表最新版本,本站同步时间存在延迟,无法保证此镜像与上游最新版本一致
生产环境建议使用明确的版本号(如 v1.2.3),避免因版本不一致导致问题。 了解更多 →

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docker.io/windj007/lama:latest
linux/amd64 docker.io

该镜像为docker.io/windj007/lama,通常用于提供lama大语言模型的运行环境,包含模型运行所需的依赖库和基础配置,方便用户快速部署并使用lama模型进行推理或相关任务处理。

13
浏览次数
7.68GB
镜像大小
国内镜像
swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest
源镜像
docker.io/windj007/lama:latest
镜像ID
sha256:d0edecbb9f73c8f02e059e47d19cd40edd707cf6d68a3b390d6bfe670e874558
镜像 TAG
latest
镜像大小
7.68GB
平台架构
linux/amd64
镜像源
docker.io
CMD
启动入口
entrypoint.sh
工作目录
/home/user
OS/平台
linux/amd64
镜像创建
2021-09-24T10:46:53.597149026Z
同步时间
2026-09-04 00:30
浏览量
13 次
贡献者
⚙️ 环境变量 23
KeyValue
PATH=/home/user/miniconda3/bin:/home/user/.local/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 0
NVARCH=x86_64 1
NVIDIA_REQUIRE_CUDA=cuda>=10.2 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441 2
NV_CUDA_CUDART_VERSION=10.2.89-1 3
NV_ML_REPO_ENABLED=1 4
NV_ML_REPO_URL=https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 5
CUDA_VERSION=10.2.89 6
LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 7
NVIDIA_VISIBLE_DEVICES=all 8
NVIDIA_DRIVER_CAPABILITIES=compute,utility 9
NV_CUDA_LIB_VERSION=10.2.89-1 10
NV_NVTX_VERSION=10.2.89-1 11
NV_LIBNPP_VERSION=10.2.89-1 12
NV_LIBCUSPARSE_VERSION=10.2.89-1 13
NV_LIBCUBLAS_PACKAGE_NAME=libcublas10 14
NV_LIBCUBLAS_VERSION=10.2.2.89-1 15
NV_LIBCUBLAS_PACKAGE=libcublas10=10.2.2.89-1 16
NV_LIBNCCL_PACKAGE_NAME=libnccl2 17
NV_LIBNCCL_PACKAGE_VERSION=2.11.4-1 18
NCCL_VERSION=2.11.4 19
NV_LIBNCCL_PACKAGE=libnccl2=2.11.4-1+cuda10.2 20
PYTHONPATH=/home/user/project 21
TORCH_HOME=/home/user/.torch 22
🏷️ 镜像标签 1
KeyValue
NVIDIA CORPORATION <cudatools@nvidia.com> maintainer
🛡️ 镜像安全扫描
ubuntu 18.04 Trivy 2026-09-04 00:31 查看完整报告
239
低危 LOW
1238
中危 MEDIUM
206
高危 HIGH
14
严重 CRITICAL
受影响目标 (3)
docker.io/windj007/lama:latest (ubuntu 18.04) ubuntu Python python-pkg /home/user/miniconda3/lib/python3.9/site-packages/skimage/data/__init__.py

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest  docker.io/windj007/lama:latest

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest  docker.io/windj007/lama:latest

Shell快速替换命令

sed -i 's#windj007/lama:latest#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest#' 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/windj007/lama:latest && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest  docker.io/windj007/lama:latest'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest  docker.io/windj007/lama:latest'

镜像构建历史


# 2021-09-24 18:46:53  0.00B 
/bin/sh -c #(nop)  ENTRYPOINT ["entrypoint.sh"]
                        
# 2021-09-24 18:46:53  21.00B 
/bin/sh -c #(nop) ADD file:3caae56a99e69ae457bbf75a750616e8abebd4ba8ec485714ae4f5453b4ab173 in /home/user/.local/bin/entrypoint.sh 
                        
# 2021-09-24 18:46:53  0.00B 
/bin/sh -c #(nop)  ENV TORCH_HOME=/home/user/.torch
                        
# 2021-09-24 18:46:53  71.98MB 
|1 USERNAME=user /bin/sh -c pip install scikit-image==0.17.2
                        
# 2021-09-24 18:43:54  5.21GB 
|1 USERNAME=user /bin/sh -c pip install numpy scipy torch==1.8.1 torchvision opencv-python tensorflow joblib matplotlib pandas     albumentations==0.5.2 pytorch-lightning==1.2.9 tabulate easydict==1.9.0 kornia==0.5.0 webdataset     packaging gpustat tqdm pyyaml hydra-core==1.1.0.dev6 scikit-learn==0.24.2 tabulate
                        
# 2021-09-24 18:40:54  10.34MB 
|1 USERNAME=user /bin/sh -c pip install -U pip
                        
# 2021-09-24 18:40:49  741.41MB 
|1 USERNAME=user /bin/sh -c wget -O /tmp/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-py39_4.9.2-Linux-x86_64.sh &&     echo "536817d1b14cb1ada88900f5be51ce0a5e042bae178b5550e62f61e223deae7c /tmp/miniconda.sh" > /tmp/miniconda.sh.sha256 &&     sha256sum --check --status < /tmp/miniconda.sh.sha256 &&     bash /tmp/miniconda.sh -bt -p "/home/$USERNAME/miniconda3" &&     rm /tmp/miniconda.sh &&     conda build purge &&     conda init
                        
# 2021-09-24 18:39:48  0.00B 
/bin/sh -c #(nop)  ENV PYTHONPATH=/home/user/project
                        
# 2021-09-24 18:39:47  0.00B 
/bin/sh -c #(nop)  ENV PATH=/home/user/miniconda3/bin:/home/user/.local/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2021-09-24 18:39:47  0.00B 
/bin/sh -c #(nop) WORKDIR /home/user
                        
# 2021-09-24 18:39:47  0.00B 
/bin/sh -c #(nop)  USER user:user
                        
# 2021-09-24 18:39:47  2.64MB 
|1 USERNAME=user /bin/sh -c apt-get install -y sudo &&     addgroup --gid 1000 $USERNAME &&     adduser --uid 1000 --gid 1000 --disabled-password --gecos '' $USERNAME &&     adduser $USERNAME sudo &&     echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers &&     USER=$USERNAME &&     GROUP=$USERNAME
                        
# 2021-09-24 18:39:44  0.00B 
/bin/sh -c #(nop)  ARG USERNAME=user
                        
# 2021-09-24 18:39:44  294.86MB 
/bin/sh -c apt-get update &&     apt-get upgrade -y &&     apt-get install -y wget mc tmux nano build-essential rsync
                        
# 2021-09-18 02:13:56  251.67KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBNCCL_PACKAGE_NAME} ${NV_LIBCUBLAS_PACKAGE_NAME} # buildkit
                        
# 2021-09-18 02:13:56  1.24GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-10-2=${NV_CUDA_LIB_VERSION}     cuda-npp-10-2=${NV_LIBNPP_VERSION}     cuda-nvtx-10-2=${NV_NVTX_VERSION}     cuda-cusparse-10-2=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-09-18 02:13:56  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-09-18 02:13:56  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.11.4-1+cuda10.2
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.11.4
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.11.4-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas10=10.2.2.89-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=10.2.2.89-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas10
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=10.2.89-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=10.2.89-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=10.2.89-1
                        
# 2021-09-18 02:13:56  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=10.2.89-1
                        
# 2021-09-18 02:09:27  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2021-09-18 02:09:27  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2021-09-18 02:09:27  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2021-09-18 02:09:27  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2021-09-18 02:09:27  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2021-09-18 02:09:27  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf &&     echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2021-09-18 02:09:27  27.18MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-10-2=${NV_CUDA_CUDART_VERSION}     cuda-compat-10-2     && ln -s cuda-10.2 /usr/local/cuda &&     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=10.2.89
                        
# 2021-09-18 02:09:16  16.53MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH}/7fa2af80.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     if [ ! -z ${NV_ML_REPO_ENABLED} ]; then echo "deb ${NV_ML_REPO_URL} /" > /etc/apt/sources.list.d/nvidia-ml.list; fi &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2021-09-18 02:09:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2021-09-18 02:09:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 NV_ML_REPO_URL
ENV NV_ML_REPO_URL=https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 NV_ML_REPO_ENABLED
ENV NV_ML_REPO_ENABLED=1
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=10.2.89-1
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=10.2 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441
                        
# 2021-09-18 02:09:16  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2021-08-31 09:20:48  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2021-08-31 09:20:48  63.14MB 
/bin/sh -c #(nop) ADD file:425a053fd043786e9454fb269d4c93c624550fb913a8c96d03ddd430b4e6c1c3 in / 
                        
                    

镜像信息

{
    "Id": "sha256:d0edecbb9f73c8f02e059e47d19cd40edd707cf6d68a3b390d6bfe670e874558",
    "RepoTags": [
        "windj007/lama:latest",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama:latest"
    ],
    "RepoDigests": [
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        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/windj007/lama@sha256:34ae5eaa638dfcd2b3b70c6accac10f9d7f643db1874bfbc59a62143f470f1f1"
    ],
    "Parent": "",
    "Comment": "",
    "Created": "2021-09-24T10:46:53.597149026Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "19.03.13",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "user:user",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/home/user/miniconda3/bin:/home/user/.local/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVARCH=x86_64",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=10.2 brand=tesla,driver\u003e=396,driver\u003c397 brand=tesla,driver\u003e=410,driver\u003c411 brand=tesla,driver\u003e=418,driver\u003c419 brand=tesla,driver\u003e=440,driver\u003c441",
            "NV_CUDA_CUDART_VERSION=10.2.89-1",
            "NV_ML_REPO_ENABLED=1",
            "NV_ML_REPO_URL=https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64",
            "CUDA_VERSION=10.2.89",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=10.2.89-1",
            "NV_NVTX_VERSION=10.2.89-1",
            "NV_LIBNPP_VERSION=10.2.89-1",
            "NV_LIBCUSPARSE_VERSION=10.2.89-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas10",
            "NV_LIBCUBLAS_VERSION=10.2.2.89-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas10=10.2.2.89-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.11.4-1",
            "NCCL_VERSION=2.11.4",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.11.4-1+cuda10.2",
            "PYTHONPATH=/home/user/project",
            "TORCH_HOME=/home/user/.torch"
        ],
        "Cmd": null,
        "Image": "sha256:8c27b0760f771371a6afa56c9e46ae21104021fa240d4758c3786810f8e64ef9",
        "Volumes": null,
        "WorkingDir": "/home/user",
        "Entrypoint": [
            "entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 7681467444,
    "GraphDriver": {
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        ]
    },
    "Metadata": {
        "LastTagTime": "2026-09-04T00:23:39.933433174+08:00"
    }
}

更多版本

docker.io/windj007/lama:latest

linux/amd64 docker.io7.68GB2026-09-04 00:30
12
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