ghcr.io/remsky/kokoro-fastapi-gpu:latest linux/amd64

ghcr.io/remsky/kokoro-fastapi-gpu:latest - 国内下载镜像源 浏览次数:18

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

```html

ghcr.io/remsky/kokoro-fastapi-gpu 镜像描述

这是一个基于 Kokoro 和 FastAPI 构建的 Docker 镜像，并支持 GPU 加速。它结合了 Kokoro 的机器学习模型部署能力和 FastAPI 的高性能 API 框架，方便用户快速部署和使用 GPU 加速的机器学习模型。 该镜像预装了必要的库和依赖，可以简化开发和部署流程。

```
源镜像 ghcr.io/remsky/kokoro-fastapi-gpu:latest
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest
镜像ID sha256:fa4b0ce39c29506f0a91e4c37d2a56b541be9277eceba5d047067d1ecd4add06
镜像TAG latest
大小 13.15GB
镜像源 ghcr.io
CMD ./entrypoint.sh
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /app
OS/平台 linux/amd64
浏览量 18 次
贡献者 54******0@qq.com
镜像创建 2025-03-07T05:30:29.182055991Z
同步时间 2025-04-25 04:22
更新时间 2025-04-26 15:28
环境变量
PATH=/app/.venv/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>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 NV_CUDA_CUDART_VERSION=12.8.57-1 CUDA_VERSION=12.8.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.8.0-1 NV_NVTX_VERSION=12.8.55-1 NV_LIBNPP_VERSION=12.3.3.65-1 NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.65-1 NV_LIBCUSPARSE_VERSION=12.5.7.53-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8 NV_LIBCUBLAS_VERSION=12.8.3.14-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.3.14-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1 NCCL_VERSION=2.25.1-1 NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8 NVIDIA_PRODUCT_NAME=CUDA NV_CUDNN_VERSION=9.7.0.66-1 NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12 NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.7.0.66-1 DEBIAN_FRONTEND=noninteractive PHONEMIZER_ESPEAK_PATH=/usr/bin PHONEMIZER_ESPEAK_DATA=/usr/share/espeak-ng-data ESPEAK_DATA_PATH=/usr/share/espeak-ng-data PYTHONUNBUFFERED=1 PYTHONPATH=/app:/app/api UV_LINK_MODE=copy USE_GPU=true DOWNLOAD_MODEL=true DEVICE=gpu
镜像标签
9.7.0.66-1: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 24.04: org.opencontainers.image.version
无权限下载?点我修复 生成Docker Run命令

Docker拉取命令 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest  ghcr.io/remsky/kokoro-fastapi-gpu:latest

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest  ghcr.io/remsky/kokoro-fastapi-gpu:latest

Shell快速替换命令 

sed -i 's#ghcr.io/remsky/kokoro-fastapi-gpu:latest#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-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/ghcr.io/remsky/kokoro-fastapi-gpu:latest && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest  ghcr.io/remsky/kokoro-fastapi-gpu:latest'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest  ghcr.io/remsky/kokoro-fastapi-gpu:latest'

镜像构建历史 


# 2025-03-07 13:30:29  0.00B 设置默认要执行的命令
CMD ["./entrypoint.sh"]
                        
# 2025-03-07 13:30:29  0.00B 设置环境变量 DEVICE
ENV DEVICE=gpu
                        
# 2025-03-07 13:30:29  327.82MB 执行命令并创建新的镜像层
RUN /bin/sh -c if [ "$DOWNLOAD_MODEL" = "true" ]; then     python download_model.py --output api/src/models/v1_0;     fi # buildkit
                        
# 2025-03-07 13:30:27  0.00B 设置环境变量 DOWNLOAD_MODEL
ENV DOWNLOAD_MODEL=true
                        
# 2025-03-07 13:30:27  0.00B 设置环境变量 PYTHONUNBUFFERED PYTHONPATH PATH UV_LINK_MODE USE_GPU
ENV PYTHONUNBUFFERED=1 PYTHONPATH=/app:/app/api PATH=/app/.venv/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin UV_LINK_MODE=copy USE_GPU=true
                        
# 2025-03-07 13:30:27  239.00B 执行命令并创建新的镜像层
RUN /bin/sh -c chmod +x ./entrypoint.sh # buildkit
                        
# 2025-03-07 13:30:27  5.69KB 复制新文件或目录到容器中
COPY --chown=appuser:appuser docker/scripts/ ./ # buildkit
                        
# 2025-03-07 13:30:27  97.78KB 复制新文件或目录到容器中
COPY --chown=appuser:appuser web ./web # buildkit
                        
# 2025-03-07 13:30:26  35.39MB 复制新文件或目录到容器中
COPY --chown=appuser:appuser api ./api # buildkit
                        
# 2025-03-07 13:30:26  7.17GB 执行命令并创建新的镜像层
RUN /bin/sh -c uv venv --python 3.10 &&     uv sync --extra gpu # buildkit
                        
# 2025-03-07 13:29:39  0.00B 设置环境变量 PHONEMIZER_ESPEAK_PATH PHONEMIZER_ESPEAK_DATA ESPEAK_DATA_PATH
ENV PHONEMIZER_ESPEAK_PATH=/usr/bin PHONEMIZER_ESPEAK_DATA=/usr/share/espeak-ng-data ESPEAK_DATA_PATH=/usr/share/espeak-ng-data
                        
# 2025-03-07 13:29:39  2.26KB 复制新文件或目录到容器中
COPY --chown=appuser:appuser pyproject.toml ./pyproject.toml # buildkit
                        
# 2025-03-07 13:29:39  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2025-03-07 13:29:39  0.00B 指定运行容器时使用的用户
USER appuser
                        
# 2025-03-07 13:29:39  10.90KB 执行命令并创建新的镜像层
RUN /bin/sh -c useradd -m -u 1001 appuser &&     mkdir -p /app/api/src/models/v1_0 &&     chown -R appuser:appuser /app # buildkit
                        
# 2025-03-07 13:29:38  39.83MB 执行命令并创建新的镜像层
RUN /bin/sh -c curl -LsSf https://astral.sh/uv/install.sh | sh &&     mv /root/.local/bin/uv /usr/local/bin/ &&     mv /root/.local/bin/uvx /usr/local/bin/ # buildkit
                        
# 2025-03-07 13:29:37  1.05GB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update && apt-get install -y     python3.10     python3-venv     espeak-ng     espeak-ng-data     git     libsndfile1     curl     ffmpeg     g++  && apt-get clean && rm -rf /var/lib/apt/lists/*  && mkdir -p /usr/share/espeak-ng-data  && ln -s /usr/lib/*/espeak-ng-data/* /usr/share/espeak-ng-data/ # buildkit
                        
# 2025-03-07 13:29:37  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2025-01-27 07:08:00  1.10GB 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
                        
# 2025-01-27 07:08:00  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=9.7.0.66-1
                        
# 2025-01-27 07:08:00  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:08:00  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:08:00  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.7.0.66-1
                        
# 2025-01-27 07:08:00  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12
                        
# 2025-01-27 07:08:00  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=9.7.0.66-1
                        
# 2025-01-27 07:06:37  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-01-27 07:06:37  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2025-01-27 07:06:37  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2025-01-27 07:06:37  239.16KB 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
                        
# 2025-01-27 07:06:37  3.13GB 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-12-8=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-8=${NV_NVTX_VERSION}     libcusparse-12-8=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:06:37  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.3.14-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.8.3.14-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.5.7.53-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.65-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.3.3.65-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.8.55-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.0-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2025-01-27 07:06:37  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-01-27 07:06:37  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
                        
# 2025-01-27 07:06:37  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
                        
# 2025-01-27 07:06:37  203.12MB 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-12-8=${NV_CUDA_CUDART_VERSION}     cuda-compat-12-8     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.8.0
                        
# 2025-01-27 07:06:37  10.24MB 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/ubuntu2404/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:06:37  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.8.57-1
                        
# 2025-01-27 07:06:37  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 brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2024-11-20 01:29:25  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2024-11-20 01:29:25  78.12MB 
/bin/sh -c #(nop) ADD file:bcebbf0fddcba5b864d5d267b68dd23bcfb01275e6ec7bcab69bf8b56af14804 in / 
                        
# 2024-11-20 01:29:23  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=24.04
                        
# 2024-11-20 01:29:23  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2024-11-20 01:29:23  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2024-11-20 01:29:23  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息 

{
    "Id": "sha256:fa4b0ce39c29506f0a91e4c37d2a56b541be9277eceba5d047067d1ecd4add06",
    "RepoTags": [
        "ghcr.io/remsky/kokoro-fastapi-gpu:latest",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/remsky/kokoro-fastapi-gpu:latest"
    ],
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更多版本

ghcr.io/remsky/kokoro-fastapi-gpu:v0.2.1

linux/amd64 ghcr.io13.15GB2025-04-18 00:44
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ghcr.io/remsky/kokoro-fastapi-gpu:latest

linux/amd64 ghcr.io13.15GB2025-04-25 04:22
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