docker.io/alphacep/kaldi-vosk-server-gpu:latest - 镜像下载

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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 →

docker.io/alphacep/kaldi-vosk-server-gpu:latest

linux/amd64 docker.io kamon_1825380 贡献

这是一个基于Kaldi语音识别工具包和Vosk语音识别库构建的Docker镜像，并支持GPU加速。

它提供了一个预先配置好的Kaldi-Vosk服务器，方便用户快速部署语音识别服务。

使用GPU加速可以显著提高语音识别的速度和效率。

该镜像适合需要进行语音识别任务的开发者和研究人员使用。

1272

浏览次数

6.53GB

镜像大小

源镜像

docker.io/alphacep/kaldi-vosk-server-gpu:latest

国内镜像

swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest

镜像ID

sha256:aa9584953dc75d64fb3d2500a10ab3a3ccbc063e7fa0dbec706115da21be7298

镜像 TAG

latest

镜像大小

6.53GB

平台架构

linux/amd64

镜像源

docker.io

项目信息

Hub 主页所有 TAG

CMD

启动入口

/opt/nvidia/nvidia_entrypoint.sh

工作目录

OS/平台

linux/amd64

镜像创建

2023-04-17T10:28:36.329330819+02:00

同步时间

2025-03-21 12:27

浏览量

1272 次

贡献者

kamon_1825380

⚙️ 环境变量 36

Key	Value
`PATH=/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>=12.1 brand=tesla,driver>=450,driver<451 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>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516 brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516 brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516 brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516 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	`2`
`NV_CUDA_CUDART_VERSION=12.1.55-1`	`3`
`NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1`	`4`
`CUDA_VERSION=12.1.0`	`5`
`LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64`	`6`
`NVIDIA_VISIBLE_DEVICES=all`	`7`
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`	`8`
`NV_CUDA_LIB_VERSION=12.1.0-1`	`9`
`NV_NVTX_VERSION=12.1.66-1`	`10`
`NV_LIBNPP_VERSION=12.0.2.50-1`	`11`
`NV_LIBNPP_PACKAGE=libnpp-12-1=12.0.2.50-1`	`12`
`NV_LIBCUSPARSE_VERSION=12.0.2.55-1`	`13`
`NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1`	`14`
`NV_LIBCUBLAS_VERSION=12.1.0.26-1`	`15`
`NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.0.26-1`	`16`
`NV_LIBNCCL_PACKAGE_NAME=libnccl2`	`17`
`NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1`	`18`
`NCCL_VERSION=2.17.1-1`	`19`
`NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1`	`20`
`NVIDIA_PRODUCT_NAME=CUDA`	`21`
`NV_CUDA_CUDART_DEV_VERSION=12.1.55-1`	`22`
`NV_NVML_DEV_VERSION=12.1.55-1`	`23`
`NV_LIBCUSPARSE_DEV_VERSION=12.0.2.55-1`	`24`
`NV_LIBNPP_DEV_VERSION=12.0.2.50-1`	`25`
`NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-1=12.0.2.50-1`	`26`
`NV_LIBCUBLAS_DEV_VERSION=12.1.0.26-1`	`27`
`NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1`	`28`
`NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-1=12.1.0.26-1`	`29`
`NV_NVPROF_VERSION=12.1.55-1`	`30`
`NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-1=12.1.55-1`	`31`
`NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev`	`32`
`NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1`	`33`
`NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.17.1-1+cuda12.1`	`34`
`LIBRARY_PATH=/usr/local/cuda/lib64/stubs`	`35`

🏷️ 镜像标签 3

Key	Value
`NVIDIA CORPORATION <cudatools@nvidia.com>`	`maintainer`
`ubuntu`	`org.opencontainers.image.ref.name`
`22.04`	`org.opencontainers.image.version`

Chatgpt|Claude一站式支持平台提供先进的AI镜像服务，助你在国内优雅的使用Chatgpt和Claude等AI服务

无权限下载？点我修复生成 Docker Run 命令生成 Kubernetes YAML

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest  docker.io/alphacep/kaldi-vosk-server-gpu:latest

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest  docker.io/alphacep/kaldi-vosk-server-gpu:latest

Shell快速替换命令

sed -i 's#alphacep/kaldi-vosk-server-gpu:latest#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu: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/alphacep/kaldi-vosk-server-gpu:latest && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest  docker.io/alphacep/kaldi-vosk-server-gpu: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/alphacep/kaldi-vosk-server-gpu:latest && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/alphacep/kaldi-vosk-server-gpu:latest  docker.io/alphacep/kaldi-vosk-server-gpu:latest'

镜像构建历史


# 2023-04-17 16:28:36  290.05MB 执行命令并创建新的镜像层
RUN |3 KALDI_MKL=0 DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC /bin/sh -c git clone -b vosk --single-branch https://github.com/alphacep/kaldi /opt/kaldi     && cd /opt/kaldi/tools     && sed -i 's:status=0:exit 0:g' extras/check_dependencies.sh     && sed -i 's:--enable-ngram-fsts:--enable-ngram-fsts --disable-bin:g' Makefile     && make -j $(nproc) openfst cub     && if [ "x$KALDI_MKL" != "x1" ] ; then           extras/install_openblas_clapack.sh;        else           extras/install_mkl.sh;        fi         && cd /opt/kaldi/src     && if [ "x$KALDI_MKL" != "x1" ] ; then           ./configure --mathlib=OPENBLAS_CLAPACK --shared;        else           ./configure --mathlib=MKL --shared;        fi     && sed -i 's:-msse -msse2:-msse -msse2:g' kaldi.mk     && sed -i 's: -O1 : -O3 :g' kaldi.mk     && make -j $(nproc) online2 lm rnnlm cudafeat cudadecoder         && pip3 install --upgrade websockets cffi         && git clone https://github.com/alphacep/vosk-api /opt/vosk-api     && cd /opt/vosk-api/src     && HAVE_CUDA=1 HAVE_MKL=$KALDI_MKL KALDI_ROOT=/opt/kaldi make -j $(nproc)     && cd /opt/vosk-api/python     && python3 ./setup.py install         && git clone https://github.com/alphacep/vosk-server /opt/vosk-server         && rm -rf /opt/vosk-api/src/*.o     && rm -rf /opt/kaldi     && rm -rf /root/.cache     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-04-17 16:14:06  176.73MB 执行命令并创建新的镜像层
RUN |3 KALDI_MKL=0 DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC /bin/sh -c apt-get update &&     apt-get install -y --no-install-recommends         wget         bzip2         unzip         xz-utils         g++         make         cmake         git         python3         python3-dev         python3-pip         zlib1g-dev         automake         autoconf         libtool         pkg-config         ca-certificates     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-04-17 16:14:06  0.00B 定义构建参数
ARG TZ=Etc/UTC
                        
# 2023-04-17 16:14:06  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2023-04-17 16:14:06  0.00B 定义构建参数
ARG KALDI_MKL
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2023-03-08 06:39:45  383.37KB 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
                        
# 2023-03-08 06:39:45  3.53GB 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}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-03-08 06:39:45  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-03-08 06:39:45  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-03-08 06:39:45  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
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.17.1-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2023-03-08 06:39:45  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
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.1.55-1
                        
# 2023-03-08 06:39:45  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
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.1.0.26-1
                        
# 2023-03-08 06:39:45  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
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.0.2.50-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.0.2.55-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.1.55-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.1.55-1
                        
# 2023-03-08 06:39:45  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.0-1
                        
# 2023-03-08 06:29:35  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-03-08 06:29:35  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-03-08 06:29:35  3.04KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-03-08 06:29:35  261.20KB 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
                        
# 2023-03-08 06:29:35  2.29GB 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
                        
# 2023-03-08 06:29:35  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-03-08 06:29:35  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.17.1-1+cuda12.1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.17.1-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.17.1-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-1=12.1.0.26-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.1.0.26-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.0.2.55-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-1=12.0.2.50-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.0.2.50-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.1.66-1
                        
# 2023-03-08 06:29:35  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.1.0-1
                        
# 2023-03-08 06:25:37  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-03-08 06:25:37  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-03-08 06:25:37  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-03-08 06:25:37  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-03-08 06:25:37  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
                        
# 2023-03-08 06:25:37  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
                        
# 2023-03-08 06:25:37  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
                        
# 2023-03-08 06:25:22  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.1.0
                        
# 2023-03-08 06:25:22  10.52MB 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
                        
# 2023-03-08 06:25:22  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-03-08 06:25:22  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-03-08 06:25:22  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-1
                        
# 2023-03-08 06:25:22  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.1.55-1
                        
# 2023-03-08 06:25:22  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 brand 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>=450,driver<451 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>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516 brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516 brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516 brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516 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
                        
# 2023-03-08 06:25:22  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2023-03-01 12:38:49  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-03-01 12:38:48  77.81MB 
/bin/sh -c #(nop) ADD file:fb4c8244f4468cdd3f666932f05805a3882d34010d3a0c14b7c20589bf619a9c in / 
                        
# 2023-03-01 12:38:47  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2023-03-01 12:38:47  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-03-01 12:38:47  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-03-01 12:38:47  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息

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}

更多版本

docker.io/alphacep/kaldi-vosk-server-gpu:latest

linux/amd64 docker.io6.53GB2025-03-21 12:27

1271

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