docker.io/huggingface/autotrain-advanced:b5c98fb linux/amd64

docker.io/huggingface/autotrain-advanced:b5c98fb - 国内下载镜像源 浏览次数:14 安全受验证的发布者-huggingface

这是一个用于AutoTrain Advanced的Docker容器镜像。AutoTrain是一个自动化机器学习平台，而Advanced版本则提供了更高级的功能和特性，允许用户进行更复杂的模型训练和部署。这个镜像包含了运行AutoTrain Advanced所需的所有依赖项和工具，方便用户快速搭建和使用该平台。

源镜像 docker.io/huggingface/autotrain-advanced:b5c98fb
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb
镜像ID sha256:f5a7820543535f6b760af6e11569eefb5f942192c2790ab485144f8b55ceb922
镜像TAG b5c98fb
大小 15.00GB
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 /app
OS/平台 linux/amd64
浏览量 14 次
贡献者 59******9@qq.com
镜像创建 2025-01-21T08:00:32.326776723Z
同步时间 2025-09-18 00:26
更新时间 2025-09-18 23:51
环境变量
PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/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>=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=12.1.105-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1 CUDA_VERSION=12.1.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.1.1-1 NV_NVTX_VERSION=12.1.105-1 NV_LIBNPP_VERSION=12.1.0.40-1 NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1 NV_LIBCUSPARSE_VERSION=12.1.0.106-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1 NV_LIBCUBLAS_VERSION=12.1.3.1-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1 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 NV_CUDNN_VERSION=8.9.0.131 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1 DEBIAN_FRONTEND=noninteractive TZ=UTC HF_HUB_ENABLE_HF_TRANSFER=1 HF_HOME=/app/.cache HOME=/app PYTHONPATH=/app/app PYTHONUNBUFFERED=1 GRADIO_ALLOW_FLAGGING=never GRADIO_NUM_PORTS=1 GRADIO_SERVER_NAME=0.0.0.0 SYSTEM=spaces
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
无权限下载?点我修复 生成Docker Run命令 生成Kubernetes YAML资源

Docker拉取命令 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb  docker.io/huggingface/autotrain-advanced:b5c98fb

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb  docker.io/huggingface/autotrain-advanced:b5c98fb

Shell快速替换命令 

sed -i 's#huggingface/autotrain-advanced:b5c98fb#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb#' 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/huggingface/autotrain-advanced:b5c98fb && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb  docker.io/huggingface/autotrain-advanced:b5c98fb'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/huggingface/autotrain-advanced:b5c98fb  docker.io/huggingface/autotrain-advanced:b5c98fb'

镜像构建历史 


# 2025-01-21 16:00:32  2.40GB 执行命令并创建新的镜像层
RUN |2 PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin conda run --no-capture-output -p /app/env /bin/bash -c pip install -e . &&     python -m nltk.downloader punkt &&     pip install -U ninja &&     pip install -U flash-attn --no-build-isolation &&     pip install -U deepspeed &&     pip install --upgrade --force-reinstall --no-cache-dir "unsloth[cu121-ampere-torch230] @ git+https://github.com/unslothai/unsloth.git" --no-deps &&     pip cache purge # buildkit
                        
# 2025-01-21 15:59:22  8.61MB 复制新文件或目录到容器中
COPY --chown=1000:1000 . /app/ # buildkit
                        
# 2025-01-21 15:59:22  7.50GB 执行命令并创建新的镜像层
RUN |2 PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin conda run --no-capture-output -p /app/env /bin/bash -c conda install pytorch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 pytorch-cuda=12.1 -c pytorch -c nvidia &&     conda clean -ya &&     conda install -c "nvidia/label/cuda-12.1.1" cuda-nvcc && conda clean -ya &&     conda install xformers -c xformers && conda clean -ya # buildkit
                        
# 2025-01-21 15:55:57  0.00B 
SHELL [conda run --no-capture-output -p /app/env /bin/bash -c]
                        
# 2025-01-21 15:55:57  368.26MB 执行命令并创建新的镜像层
RUN |2 PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c conda create -p /app/env -y python=3.10 # buildkit
                        
# 2025-01-21 15:55:50  0.00B 设置环境变量 PATH
ENV PATH=/app/miniconda/bin:/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-21 15:55:50  640.14MB 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh     && sh Miniconda3-latest-Linux-x86_64.sh -b -p /app/miniconda     && rm -f Miniconda3-latest-Linux-x86_64.sh # buildkit
                        
# 2025-01-21 15:55:42  0.00B 设置环境变量 PYTHONPATH PYTHONUNBUFFERED GRADIO_ALLOW_FLAGGING GRADIO_NUM_PORTS GRADIO_SERVER_NAME SYSTEM
ENV PYTHONPATH=/app/app PYTHONUNBUFFERED=1 GRADIO_ALLOW_FLAGGING=never GRADIO_NUM_PORTS=1 GRADIO_SERVER_NAME=0.0.0.0 SYSTEM=spaces
                        
# 2025-01-21 15:55:42  0.00B 设置环境变量 HOME
ENV HOME=/app
                        
# 2025-01-21 15:55:42  0.00B 指定运行容器时使用的用户
USER user
                        
# 2025-01-21 15:55:42  0.00B 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c chown -R user:user /app # buildkit
                        
# 2025-01-21 15:55:42  333.77KB 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c useradd -m -u 1000 user # buildkit
                        
# 2025-01-21 15:55:42  0.00B 设置环境变量 HF_HOME
ENV HF_HOME=/app/.cache
                        
# 2025-01-21 15:55:42  0.00B 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c mkdir -p /app/.cache # buildkit
                        
# 2025-01-21 15:55:42  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2025-01-21 15:55:42  62.31MB 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash &&     git lfs install # buildkit
                        
# 2025-01-21 15:55:34  643.39MB 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c apt-get update &&      apt-get upgrade -y &&      apt-get install -y     build-essential     cmake     curl     ca-certificates     gcc     git     locales     net-tools     wget     libpq-dev     libsndfile1-dev     git     git-lfs     libgl1     unzip     libjpeg-dev     libpng-dev     libgomp1     && rm -rf /var/lib/apt/lists/* &&     apt-get clean # buildkit
                        
# 2025-01-21 15:55:09  0.00B 执行命令并创建新的镜像层
RUN |2 PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin /bin/sh -c mkdir -p /tmp/model &&     chown -R 1000:1000 /tmp/model &&     mkdir -p /tmp/data &&     chown -R 1000:1000 /tmp/data # buildkit
                        
# 2025-01-21 15:55:09  0.00B 定义构建参数
ARG PATH=/app/ngc-cli:/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-21 15:55:09  0.00B 设置环境变量 PATH
ENV PATH=/app/ngc-cli:/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-21 15:55:09  0.00B 定义构建参数
ARG PATH=/miniconda3/bin:/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-21 15:55:09  0.00B 设置环境变量 PATH
ENV PATH=/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-21 15:55:09  0.00B 设置环境变量 DEBIAN_FRONTEND TZ HF_HUB_ENABLE_HF_TRANSFER
ENV DEBIAN_FRONTEND=noninteractive TZ=UTC HF_HUB_ENABLE_HF_TRANSFER=1
                        
# 2023-11-10 13:42:50  1.14GB 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}     && apt-mark hold ${NV_CUDNN_PACKAGE_NAME}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 13:42:50  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.0.131
                        
# 2023-11-10 13:42:50  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:42:50  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:42:50  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 13:42:50  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2023-11-10 13:42:50  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.0.131
                        
# 2023-11-10 13:13:35  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 13:13:35  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 13:13:35  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 13:13:35  261.40KB 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 13:13:35  2.01GB 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 13:13:35  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:13:35  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:13:35  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 13:13:35  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.3.1-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.1.0.106-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.1.0.40-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.105-1
                        
# 2023-11-10 13:13:35  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.1-1
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 13:08:12  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 13:08:12  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 13:08:12  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 13:08:12  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 13:08:12  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 13:08:11  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 13:07:58  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.1
                        
# 2023-11-10 13:07:58  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 13:07:58  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 13:07:58  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-11-10 13:07:58  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.105-1
                        
# 2023-11-10 13:07:58  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 13:07:58  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 

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    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-01-21T08:00:32.326776723Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "user",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
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            "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=12.1.105-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1",
            "CUDA_VERSION=12.1.1",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=12.1.1-1",
            "NV_NVTX_VERSION=12.1.105-1",
            "NV_LIBNPP_VERSION=12.1.0.40-1",
            "NV_LIBNPP_PACKAGE=libnpp-12-1=12.1.0.40-1",
            "NV_LIBCUSPARSE_VERSION=12.1.0.106-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1",
            "NV_LIBCUBLAS_VERSION=12.1.3.1-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.3.1-1",
            "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",
            "NV_CUDNN_VERSION=8.9.0.131",
            "NV_CUDNN_PACKAGE_NAME=libcudnn8",
            "NV_CUDNN_PACKAGE=libcudnn8=8.9.0.131-1+cuda12.1",
            "DEBIAN_FRONTEND=noninteractive",
            "TZ=UTC",
            "HF_HUB_ENABLE_HF_TRANSFER=1",
            "HF_HOME=/app/.cache",
            "HOME=/app",
            "PYTHONPATH=/app/app",
            "PYTHONUNBUFFERED=1",
            "GRADIO_ALLOW_FLAGGING=never",
            "GRADIO_NUM_PORTS=1",
            "GRADIO_SERVER_NAME=0.0.0.0",
            "SYSTEM=spaces"
        ],
        "Cmd": null,
        "Image": "",
        "Volumes": null,
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        "Entrypoint": [
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            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
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    "Size": 14999903910,
    "GraphDriver": {
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        "LastTagTime": "2025-09-18T00:14:50.205103179+08:00"
    }
}

更多版本

docker.io/huggingface/autotrain-advanced:b5c98fb

linux/amd64 docker.io15.00GB2025-09-18 00:26
13