docker.io/qwenllm/qwenvl:2.5-cu121 linux/amd64

docker.io/qwenllm/qwenvl:2.5-cu121 - 国内下载镜像源 浏览次数:246
```html

该镜像 docker.io/qwenllm/qwenvl 提供了QwenLLM模型的运行环境。 它包含了运行QwenLLM所需的所有依赖项和配置,方便用户快速部署和使用QwenLLM模型。

```
源镜像 docker.io/qwenllm/qwenvl:2.5-cu121
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121
镜像ID sha256:83e0e4ecdfa2abef8d539b506b2720d5a3b94d78b8478716b7b0632f9ced9880
镜像TAG 2.5-cu121
大小 21.26GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /data/shared/Qwen/
OS/平台 linux/amd64
浏览量 246 次
贡献者
镜像创建 2025-02-07T12:17:33.800755728+08:00
同步时间 2025-03-09 08:52
更新时间 2025-04-05 01:39
开放端口
80/tcp
环境变量
PATH=/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>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 NV_CUDA_CUDART_VERSION=12.1.55-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1 CUDA_VERSION=12.1.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.1.0-1 NV_NVTX_VERSION=12.1.66-1 NV_LIBNPP_VERSION=12.0.2.50-1 NV_LIBNPP_PACKAGE=libnpp-12-1=12.0.2.50-1 NV_LIBCUSPARSE_VERSION=12.0.2.55-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1 NV_LIBCUBLAS_VERSION=12.1.0.26-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.0.26-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1 NCCL_VERSION=2.17.1-1 NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1 NVIDIA_PRODUCT_NAME=CUDA NVIDIA_CUDA_END_OF_LIFE=1 NV_CUDA_CUDART_DEV_VERSION=12.1.55-1 NV_NVML_DEV_VERSION=12.1.55-1 NV_LIBCUSPARSE_DEV_VERSION=12.0.2.55-1 NV_LIBNPP_DEV_VERSION=12.0.2.50-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.0.2.50-1 NV_LIBCUBLAS_DEV_VERSION=12.1.0.26-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.0.26-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.0-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.0-1 NV_NVPROF_VERSION=12.1.55-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.55-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.9.0.131 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1 CCACHE_DIR=/root/.cache/ccache MAX_JOBS=4 NVCC_THREADS=1 VLLM_FA_CMAKE_GPU_ARCHES=80-real;90-real
镜像标签
8.9.0.131: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121  docker.io/qwenllm/qwenvl:2.5-cu121

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121  docker.io/qwenllm/qwenvl:2.5-cu121

Shell快速替换命令

sed -i 's#qwenllm/qwenvl:2.5-cu121#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121#' 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/qwenllm/qwenvl:2.5-cu121 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121  docker.io/qwenllm/qwenvl:2.5-cu121'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121  docker.io/qwenllm/qwenvl:2.5-cu121'

镜像构建历史


# 2025-02-07 12:17:33  0.00B 声明容器运行时监听的端口
EXPOSE map[80/tcp:{}]
                        
# 2025-02-07 12:17:33  40.72KB 复制新文件或目录到容器中
COPY ../web_demo_streaming ./web_demo_streaming # buildkit
                        
# 2025-02-07 12:17:33  11.39KB 复制新文件或目录到容器中
COPY ../web_demo_mm.py ./ # buildkit
                        
# 2025-02-07 12:17:33  0.00B 执行命令并创建新的镜像层
RUN |2 BUNDLE_FLASH_ATTENTION=true BUNDLE_VLLM=true /bin/sh -c rm -rvf /root/.cache/pip # buildkit
                        
# 2025-02-07 12:17:33  412.16MB 执行命令并创建新的镜像层
RUN |2 BUNDLE_FLASH_ATTENTION=true BUNDLE_VLLM=true /bin/sh -c pip3 install     gradio==5.4.0     gradio_client==1.4.2     transformers-stream-generator==0.0.4     av # buildkit
                        
# 2025-02-07 07:08:39  2.25GB 执行命令并创建新的镜像层
RUN |2 BUNDLE_FLASH_ATTENTION=true BUNDLE_VLLM=true /bin/sh -c if [ "$BUNDLE_VLLM" = "true" ]; then mkdir -p /data/shared/code     && cd /data/shared/code     && git clone https://github.com/vllm-project/vllm.git     && cd vllm     && git checkout bf3b79efb82676219a3275764d8fcf4c70097ce5     && pip3 install -r requirements-cuda.txt     && pip3 install setuptools-scm     && pip3 install . -vvv     && cd /data/shared/Qwen     && rm -rf /data/shared/code/vllm; fi # buildkit
                        
# 2025-02-07 01:10:23  0.00B 设置环境变量 CCACHE_DIR
ENV CCACHE_DIR=/root/.cache/ccache
                        
# 2025-02-07 01:10:23  0.00B 设置环境变量 VLLM_FA_CMAKE_GPU_ARCHES
ENV VLLM_FA_CMAKE_GPU_ARCHES=80-real;90-real
                        
# 2025-02-07 01:10:23  0.00B 设置环境变量 NVCC_THREADS
ENV NVCC_THREADS=1
                        
# 2025-02-07 01:10:23  0.00B 设置环境变量 MAX_JOBS
ENV MAX_JOBS=4
                        
# 2025-02-07 01:10:23  0.00B 定义构建参数
ARG BUNDLE_VLLM=true
                        
# 2025-02-07 01:10:23  604.48MB 执行命令并创建新的镜像层
RUN |1 BUNDLE_FLASH_ATTENTION=true /bin/sh -c if [ "$BUNDLE_FLASH_ATTENTION" = "true" ]; then     pip3 install --no-cache-dir --no-build-isolation flash-attn==2.7.2.post1; fi # buildkit
                        
# 2025-02-07 01:09:56  0.00B 设置环境变量 CCACHE_DIR
ENV CCACHE_DIR=/root/.cache/ccache
                        
# 2025-02-07 01:09:56  0.00B 定义构建参数
ARG BUNDLE_FLASH_ATTENTION=true
                        
# 2025-02-07 01:09:56  114.01MB 执行命令并创建新的镜像层
RUN /bin/sh -c cd ./qwen-vl-utils    && pip3 install --no-cache-dir . # buildkit
                        
# 2025-02-07 01:09:48  24.18KB 复制新文件或目录到容器中
COPY ../qwen-vl-utils ./qwen-vl-utils # buildkit
                        
# 2025-02-07 01:09:48  106.69MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install git+https://github.com/huggingface/transformers@f3f6c86582611976e72be054675e2bf0abb5f775      && pip3 install accelerate # buildkit
                        
# 2025-02-07 01:09:16  5.22GB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 xformers==0.0.28.post3 --index-url https://download.pytorch.org/whl/cu121 # buildkit
                        
# 2025-02-07 01:04:26  12.68MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install networkx==3.1 # buildkit
                        
# 2025-02-06 23:06:51  0.00B 设置工作目录为/data/shared/Qwen/
WORKDIR /data/shared/Qwen/
                        
# 2025-02-06 23:06:51  0.00B 执行命令并创建新的镜像层
RUN /bin/sh -c mkdir -p /data/shared/Qwen # buildkit
                        
# 2025-02-06 23:06:50  0.00B 设置工作目录为/
WORKDIR /
                        
# 2025-02-06 23:06:50  126.00B 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c git lfs install # buildkit
                        
# 2025-02-06 23:06:50  16.00B 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c ln -s /usr/bin/python3 /usr/bin/python # buildkit
                        
# 2025-02-06 23:06:50  135.03MB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c wget https://github.com/Kitware/CMake/releases/download/v3.26.1/cmake-3.26.1-Linux-x86_64.sh     -q -O /tmp/cmake-install.sh     && chmod u+x /tmp/cmake-install.sh     && mkdir /opt/cmake-3.26.1     && /tmp/cmake-install.sh --skip-license --prefix=/opt/cmake-3.26.1     && rm /tmp/cmake-install.sh     && ln -s /opt/cmake-3.26.1/bin/* /usr/local/bin # buildkit
                        
# 2025-02-06 23:06:42  2.92GB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c apt update -y && apt upgrade -y && apt install -y --no-install-recommends  \
    git \
    git-lfs \
    python3 \
    python3-pip \
    python3-dev \
    wget \
    vim \
    libsndfile1 \
    ccache \
    software-properties-common \
&& rm -rf /var/lib/apt/lists/*
 # buildkit
                        
# 2025-02-06 23:06:42  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2023-11-10 14:28:19  2.45GB 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     ${NV_CUDNN_PACKAGE}     ${NV_CUDNN_PACKAGE_DEV}     && apt-mark hold ${NV_CUDNN_PACKAGE_NAME}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:28:19  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
                        
# 2023-11-10 14:28:19  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:28:19  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:28:19  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 14:28:19  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1
                        
# 2023-11-10 14:28:19  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 14:28:19  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
                        
# 2023-11-10 14:02:16  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-11-10 14:02:16  385.64KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
                        
# 2023-11-10 14:02:04  4.81GB 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-dev-12-1=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-1=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-1=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-1=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-1=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-1=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:02:04  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:02:04  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.55-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.55-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.0-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.0-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.0.26-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.0.26-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.0.2.50-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.0.2.50-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.0.2.55-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.55-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.55-1
                        
# 2023-11-10 14:02:04  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.0-1
                        
# 2023-11-10 13:49:20  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 13:49:20  0.00B 设置环境变量 NVIDIA_CUDA_END_OF_LIFE
ENV NVIDIA_CUDA_END_OF_LIFE=1
                        
# 2023-11-10 13:49:20  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 13:49:20  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 13:49:20  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-11-10 13:49:20  261.38KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2023-11-10 13:49:19  1.99GB 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-12-1=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-1=${NV_NVTX_VERSION}     libcusparse-12-1=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:49:19  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:49:19  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.0.26-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.0.26-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.0.2.55-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.0.2.50-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.0.2.50-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.66-1
                        
# 2023-11-10 13:49:19  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.0-1
                        
# 2023-11-10 13:44:29  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 13:44:29  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 13:44:29  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 13:44:29  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-10 13:44:29  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
                        
# 2023-11-10 13:44:29  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
                        
# 2023-11-10 13:44:29  149.59MB 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-12-1=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:44:18  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.0
                        
# 2023-11-10 13:44:18  10.56MB 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 -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.0-1_all.deb &&     dpkg -i cuda-keyring_1.0-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:44:18  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:44:18  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:44:18  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-11-10 13:44:18  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.55-1
                        
# 2023-11-10 13:44:18  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
                        
# 2023-11-10 13:44:18  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-10-05 15:33:32  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-05 15:33:32  77.82MB 
/bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in / 
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-05 15:33:30  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

{
    "Id": "sha256:83e0e4ecdfa2abef8d539b506b2720d5a3b94d78b8478716b7b0632f9ced9880",
    "RepoTags": [
        "qwenllm/qwenvl:2.5-cu121",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl:2.5-cu121"
    ],
    "RepoDigests": [
        "qwenllm/qwenvl@sha256:d082165a6bc53db52055a8d8d3710e1dc82d6898440b910c7cfd03decdd12476",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/qwenllm/qwenvl@sha256:0085fa189ca1a8079193f97537854cd0585d3222c456e76086db68c4df7f697b"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-02-07T12:17:33.800755728+08:00",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "80/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/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=12.1 brand=tesla,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=geforce,driver\u003e=470,driver\u003c471 brand=geforcertx,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=titan,driver\u003e=470,driver\u003c471 brand=titanrtx,driver\u003e=470,driver\u003c471 brand=tesla,driver\u003e=525,driver\u003c526 brand=unknown,driver\u003e=525,driver\u003c526 brand=nvidia,driver\u003e=525,driver\u003c526 brand=nvidiartx,driver\u003e=525,driver\u003c526 brand=geforce,driver\u003e=525,driver\u003c526 brand=geforcertx,driver\u003e=525,driver\u003c526 brand=quadro,driver\u003e=525,driver\u003c526 brand=quadrortx,driver\u003e=525,driver\u003c526 brand=titan,driver\u003e=525,driver\u003c526 brand=titanrtx,driver\u003e=525,driver\u003c526",
            "NV_CUDA_CUDART_VERSION=12.1.55-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1",
            "CUDA_VERSION=12.1.0",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.1.0-1",
            "NV_NVTX_VERSION=12.1.66-1",
            "NV_LIBNPP_VERSION=12.0.2.50-1",
            "NV_LIBNPP_PACKAGE=libnpp-12-1=12.0.2.50-1",
            "NV_LIBCUSPARSE_VERSION=12.0.2.55-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1",
            "NV_LIBCUBLAS_VERSION=12.1.0.26-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.0.26-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1",
            "NCCL_VERSION=2.17.1-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NVIDIA_CUDA_END_OF_LIFE=1",
            "NV_CUDA_CUDART_DEV_VERSION=12.1.55-1",
            "NV_NVML_DEV_VERSION=12.1.55-1",
            "NV_LIBCUSPARSE_DEV_VERSION=12.0.2.55-1",
            "NV_LIBNPP_DEV_VERSION=12.0.2.50-1",
            "NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.0.2.50-1",
            "NV_LIBCUBLAS_DEV_VERSION=12.1.0.26-1",
            "NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1",
            "NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.0.26-1",
            "NV_CUDA_NSIGHT_COMPUTE_VERSION=12.1.0-1",
            "NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-1=12.1.0-1",
            "NV_NVPROF_VERSION=12.1.55-1",
            "NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.55-1",
            "NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
            "NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1",
            "NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
            "NV_CUDNN_VERSION=8.9.0.131",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1",
            "NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.0.131-1+cuda12.1",
            "CCACHE_DIR=/root/.cache/ccache",
            "MAX_JOBS=4",
            "NVCC_THREADS=1",
            "VLLM_FA_CMAKE_GPU_ARCHES=80-real;90-real"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/data/shared/Qwen/",
        "Entrypoint": [
            "/opt/nvidia/nvidia_entrypoint.sh"
        ],
        "OnBuild": null,
        "Labels": {
            "com.nvidia.cudnn.version": "8.9.0.131",
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "22.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 21256317098,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/c18bd788456085e41e97ac69d58d68d2553f7abe61d5859584c90fbe0720a01a/diff:/var/lib/docker/overlay2/1bd6fbe985f217efaa7c7e601754e1f6fd13981f60a19ca9df6e4d64371ebbb2/diff:/var/lib/docker/overlay2/4b146febafd040caf111f0892a26bc9dae4712f8ed84698134be4ef545beb6ab/diff:/var/lib/docker/overlay2/2d05d05048d528d33536c585d9d5d60d15f54042f1f240810f4b637df70bdb00/diff:/var/lib/docker/overlay2/4c0379d07e920c53b22fe68e24f240107b2d104cba695c93337eda497f2344b8/diff:/var/lib/docker/overlay2/7e4ac537fcd3e8b1ca29f719f84622c0718d1da9506e0527eabd132d1483a74a/diff:/var/lib/docker/overlay2/64a993090d77c18993dafd02fcd2861b3abe1bbaa485b137e16fd0d6d5ea0d29/diff:/var/lib/docker/overlay2/a993a65fa9760ddc12af827fdd052a590d116bdde60c1e71539c6068c10dfcfa/diff:/var/lib/docker/overlay2/368ad1330c41bf0fbc1d54c5be3c1bc24e9e0f20ecaaf03a329647df7dad2c47/diff:/var/lib/docker/overlay2/463dd15517780908f99bc0e81e1328503404cc67f7bedc2d222b93dd5ab6da3a/diff:/var/lib/docker/overlay2/96515696aafc6105c79ea59dff688070c6db845fca1b890ca03a7ddd4813f113/diff:/var/lib/docker/overlay2/2be91b9187e35a60e58c58323e20ccffe0e570e6e456e61bc0163089f6590dd6/diff:/var/lib/docker/overlay2/fb0a2c647a41351f2a71bf451d082fb449130232a459e6ae8dcd97c9931b267c/diff:/var/lib/docker/overlay2/ae04f06b3b64bcc4f7cd66707173f282b2801e97bd33f8a5d5b3adf8a217ee9e/diff:/var/lib/docker/overlay2/a81ebecd3978829f43d920cad813431b312b1de082a2c255abe11353b965283d/diff:/var/lib/docker/overlay2/133b49bb30c5c4a23fc18100ac6b1a78f457780b8a9e8db5346d974e59857bb3/diff:/var/lib/docker/overlay2/883824e01396a1e3c54cd5c5234a8ae8bc2efbf1e324264115c3bb4d0e37ca5f/diff:/var/lib/docker/overlay2/3d944046ef89554079c18189123e60296e6f7bdde8f04b866bc6a9a594f0aaeb/diff:/var/lib/docker/overlay2/05689dc0e407c0b9fef2847cc7a3436f1fa46b1a82f74c81577a3db2cce44517/diff:/var/lib/docker/overlay2/ad9909645812c361e364bef3d3d61ae213a9a0041fe70d565729395c475803b8/diff:/var/lib/docker/overlay2/3c6d5ea9f0137b810f2c5e9b2257e63f58baacba2c75b4c4722277357320216b/diff:/var/lib/docker/overlay2/2a4834c047db7ca33b0935fcf59cac785026edf2e275d07c484267f9dc406a9a/diff:/var/lib/docker/overlay2/6b5a2a88bc3906ccf1dd2ff2b3a48162e98f477f8153c2a3f46a4803c2a30c64/diff:/var/lib/docker/overlay2/86c98ab0ed88b61b06cf59d67d016cbf05a2c7cea2a7a4fe53a6be12a6bb87d7/diff:/var/lib/docker/overlay2/dddcc2c36b2b15125b046f443eaf956385215dd4fe1629756f29c2e1077ee125/diff:/var/lib/docker/overlay2/7c0ec148c160c668fe5b36bcb65f7d5badb55eb5dcdea8490e826c2a41b578a9/diff:/var/lib/docker/overlay2/b213e3c8abc27592f101ffbb1d0f2c437b5effe9b384d0f550f46a4f894f180d/diff:/var/lib/docker/overlay2/f2905627b4505cda033dd62b5a5dc1676edda5a6e1bda7cd6e6e2048fcf5aee0/diff",
            "MergedDir": "/var/lib/docker/overlay2/6a67d2bb289ac7a21c1ea24147d90b0a246038e713f49bc44fc342d169395f71/merged",
            "UpperDir": "/var/lib/docker/overlay2/6a67d2bb289ac7a21c1ea24147d90b0a246038e713f49bc44fc342d169395f71/diff",
            "WorkDir": "/var/lib/docker/overlay2/6a67d2bb289ac7a21c1ea24147d90b0a246038e713f49bc44fc342d169395f71/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:256d88da41857db513b95b50ba9a9b28491b58c954e25477d5dad8abb465430b",
            "sha256:7b9433fba79bfc9269aab8277ea9975364db1c1f775a7ee6b14b5dffa045b294",
            "sha256:765423415d690bf8ca1510e7147d5b86dba15dcf1a3b1a515f1a85cc5dd439bb",
            "sha256:e4b1bddcbe6378dfa58bf1faa040813b74938129eb4bb06cbf083240335c5c54",
            "sha256:cd77f58b80cdcfac5fcdef06b2033fedc1115073afae035a14b6692cb5cd6650",
            "sha256:8d113b7b997c1bc18469d2373662f02c8bbcf7182f8c5d8e0e1eea082cc234a4",
            "sha256:40f0eb1871b906cf31a54649bf4f7657e2a60da6d6a9adfb8598a469b8495e77",
            "sha256:6ac15100dff644720d396a534fcd373774b1aefca621211930855e5db5ebae52",
            "sha256:600c676771a0a21056d45f5fb4441c538380564d4a7127a41e260d74fc6b0519",
            "sha256:57b23d1076fd4d119609493ebbd5b837d9553387d081148c8d908f1245e2bb55",
            "sha256:6667c783780703607df00f8f7dafcfd77402d54db003c392f3ea743f9eabe359",
            "sha256:8f9b3bf612fd6c74b7fc633bddfd6986991d5b18a4fd3e79994e8d82abfc089d",
            "sha256:bd5dd740a9b770a9e7cdbf4bcc6e89a70438f90fdc7d45f767134bcdf63417b2",
            "sha256:c2f53df15a64bbe1b938114fd79767e6834ba559f6b353f9fed852b06c4cb7a4",
            "sha256:0387ae1ad50cc14a9cb20d86d40840bb0f0774538c791091d917c72c1a17e72b",
            "sha256:2f9b5b449fdf9fdea1b226b77efcb52d96507bc6e208541ed3d984903dce14e8",
            "sha256:9b2f42fbeba95f567d33c4f56e29dbb76258ce46e63e50a9a33321ab596a2f3a",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:c530836f3f41250afe83b73da93e9cf55a832443a8a807c8772a70bb83050426",
            "sha256:636181aece02db2d327dfd89a5b46d8fbe6fe88d0a65485eebc7cbc537d41fa5",
            "sha256:7833949b5b54c4cbf46c83b734968e37ca0d63e1fc10980debc630e502ed924f",
            "sha256:60dbdbe6468bde6f8961a2934b03b7f50d8d4869557841ec07f0409c37a1bf80",
            "sha256:dea2823cc5fb9cce8e61fafeb19990ee54df1ed13e147ebd7e8aa3bfa9a1fced",
            "sha256:a16c684fe43b7b32253561083d775d94f37cf6507239c75809e87da75e29d528",
            "sha256:9a6a921e8456fc6f092d07153533f8d7c2135d45e6792e0db8ea274b68b25a27",
            "sha256:425f8a356e890d1baa058eb6afd9455dab0007444efe34975f6690ceebe0a684",
            "sha256:2f754860183324a7ef2dd634b6aebbbe7948edc6d7ea9b61a233adf68ea41278",
            "sha256:68cb516b9f80ee095c48d28ac24881b5ea39ab674b9d82811c56601e3e3b33df",
            "sha256:122c966b80480b3364a68a7a7d3362c42733662b887b8677e75d46b853566f27"
        ]
    },
    "Metadata": {
        "LastTagTime": "2025-03-09T08:52:38.088047651+08:00"
    }
}

更多版本

docker.io/qwenllm/qwenvl:2.5-cu121

linux/amd64 docker.io21.26GB2025-03-09 08:52
245