NVIDIA
NVIDIA
NeMo Framework Megatron Backend
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NVIDIA
NVIDIA
NeMo Framework Megatron Backend

NVIDIA NeMo™ framework Megatron backend supports pre-training, post-training, and reinforcement learning of LLMs and multi-modal generative AI models with state-of-the-art data processing, model training techniques, and flexible deployment options.

  • LayerLabelCreated
    sha256:d847fd99b38ecba3a116909ce5632a630c7cec1541a2d8c5e06cb057cd61300fCONFIG
    05/09/2024 9:59 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.ref=
    04/22/2024 9:55 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_REF
    04/22/2024 9:55 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=82611821
    04/22/2024 9:55 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=82611821
    04/22/2024 9:55 AM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID
    04/22/2024 9:55 AM UTC
    sha256:51608a2bc20e2d07f38952642039c34da187817379a5feb21ef15e9e1fcc9137RUN
    chmod -R a+w /workspace
    04/22/2024 9:55 AM UTC
    sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1WORKDIR
    /workspace
    04/22/2024 9:55 AM UTC
    sha256:de80342d2f038e0a326a8425816dbde6bd1af3ab507f160e69d89da8ed58da90RUN
    TCNN_CUDA_ARCHITECTURES="52,60,61,70,75,80,86,89,90" pip install --no-cache-dir git+https://github.com/NVlabs/tiny-cuda-nn@6f018a9cd1b369bcb247e1d539968db8e48b2b3f#subdirectory=bindings/torch
    04/22/2024 9:55 AM UTC
    sha256:ec6035c074a959d080060acb0d5867a6d315c954071baf0dedee56e115605dc9RUN
    cd /tmp &&
      git clone https://github.com/ashawkey/stable-dreamfusion.git &&
      cd stable-dreamfusion &&
      git checkout 5550b91862a3af7842bb04875b7f1211e5095a63 &&
      find . -type f -name 'setup.py' -exec sed -i 's/c++14/c++17/g' {} + &&
      pip install --no-cache-dir ./raymarching &&
      pip install --no-cache-dir ./shencoder &&
      pip install --no-cache-dir ./freqencoder &&
      TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6 9.0+PTX" pip install --no-cache-dir ./gridencoder &&
      cd /opt &&
      rm -rf /tmp/stable-dreamfusion
    04/22/2024 9:04 AM UTC
    ...

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