NVIDIA
TensorRT LLM Develop
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NVIDIA
TensorRT LLM Develop

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.

  • LayerLabelCreated
    sha256:5f5fc4dcd2aef0f4a5529537c10f07a424c3b363d45c96eb3ead6a0e460783e4RUN
    SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip TRT_LLM_VER=1.2.0rc5 TARGETARCH=amd64 /bin/bash -c bash /tmp/generate_container_oss_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}" &&
      rm /tmp/generate_container_oss_attribution.sh
    12/08/2025 2:35 AM UTC
    sha256:d27917487ba683de0eaf9b67f4bde69bb259cff6398b80b585db7705c6355cceCOPY
    scripts/generate_container_oss_attribution.sh /tmp/generate_container_oss_attribution.sh
    12/08/2025 2:35 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TARGETARCH=amd64
    12/08/2025 2:35 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TRT_LLM_VER=1.2.0rc5
    12/08/2025 2:35 AM UTC
    sha256:178d08ea76ae56f760030615672e3204b86b650b259893e84f0f5b63882af498RUN
    SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip /bin/bash -c GITHUB_MIRROR=${GITHUB_MIRROR} bash ./install_ucx.sh &&
      GITHUB_MIRROR=${GITHUB_MIRROR} bash ./install_nixl.sh &&
      bash ./install_etcd.sh &&
      rm install_ucx.sh &&
      rm install_nixl.sh &&
      rm install_etcd.sh
    12/08/2025 2:35 AM UTC
    sha256:e9d441f0f9cfed05d8269edbde896e6109a7d22eccdc73175212536cc147cecdRUN
    SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip /bin/bash -c GITHUB_MIRROR=${GITHUB_MIRROR} PYTHON_VERSION=${PYTHON_VERSION} TRT_VER=${TRT_VER} CUDA_VER=${CUDA_VER} CUDNN_VER=${CUDNN_VER} NCCL_VER=${NCCL_VER} CUBLAS_VER=${CUBLAS_VER} TORCH_INSTALL_TYPE=${TORCH_INSTALL_TYPE} bash ./install.sh --base --cmake --ccache --cuda_toolkit --tensorrt --polygraphy --mpi4py --pytorch --opencv &&
      rm install_base.sh &&
      rm install_cmake.sh &&
      rm install_ccache.sh &&
      rm install_cuda_toolkit.sh &&
      rm install_tensorrt.sh &&
      rm install_polygraphy.sh &&
      rm install_mpi4py.sh &&
      rm install_pytorch.sh &&
      rm install.sh
    12/08/2025 2:34 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TORCH_INSTALL_TYPE=skip
    12/08/2025 2:24 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    CUBLAS_VER
    12/08/2025 2:24 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NCCL_VER
    12/08/2025 2:24 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    CUDNN_VER
    12/08/2025 2:24 AM UTC
    ...

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