ContainersNVIDIADeepSeek-R1NVIDIALlama-3.1-Nemotron-70B-InstructNVIDIAPyTorch
CollectionsNVIDIAOmniverse Kit (FB)NVIDIADeepStream SDKNVIDIAOmniverse Kit App Streaming
ModelsNVIDIAStyleGAN3 pretrained modelsNVIDIAPeopleNetNVIDIATrafficCamNet
ResourcesNVIDIARiva Skills Quick Start
Helm ChartsNVIDIAGPU OperatorNVIDIANVIDIA NIM Operator
  • NVIDIA
    Merlin PyTorch
    Container
    NVIDIA
    Merlin PyTorch

    The Merlin PyTorch container allows users to do preprocessing and feature engineering with NVTabular, and then train a deep-learning based recommender system model with PyTorch, and serve the trained model on Triton Inference Server.

  • LayerLabelCreated
    sha256:0dff698982060e4dd17ed52b7f2285c9f691fb50cfc17cbba1d3722520470390RUN
    pip install --no-cache-dir matplotlib
    		04/27/2023 8:02 AM UTC
    sha256:d276c5b8db2807865ae906937bbaa3661f66e77873dc1621261774eaf6234d18RUN
    ln -s /opt/tritonserver/backends/pytorch/* /usr/local/lib/
    		04/27/2023 8:02 AM UTC
    sha256:a457688fb920bd03b7f1a1cb1eb2b7a77cddc65a28c4cd6a0f848e0d7df1eb0fCOPY
    --chown=1000:1000dir:41e5b2af01ec677f7794601e0ce75f8f9f556e54e93130327a5417fb7ff58ec1 in /usr/local/lib/python3.8/dist-packages/torch.egg-info/
    		04/27/2023 8:02 AM UTC
    sha256:b17007f8d600b835704e6262a95a80f869a6a5622c632da39cea35351ab7c2d5COPY
    --chown=1000:1000dir:b2533420e33d8337afde9d69ec6d5ff238705ae597848613d2e87b98aa759ecf in /usr/local/lib/python3.8/dist-packages/numpy.dist-info/
    		04/27/2023 8:02 AM UTC
    sha256:511c1eea7438d1fafd2792387d02592ef0a38d0a01b405d1548880e0d5deac71COPY
    --chown=1000:1000dir:4169deef179af3fe4bada7e86e5238911cef9455eb4ddac2865576eaf863bc49 in /usr/local/lib/python3.8/dist-packages/numba.dist-info/
    		04/27/2023 8:01 AM UTC
    sha256:284ebf647787599f1b752ed7c4fd95695eef158626ee650c437cf6db120313b7COPY
    --chown=1000:1000dir:211e5315f6a46f8c430a669a8d36e3ec0135dcb6b4454da5cf6be67850c65da3 in /usr/local/lib/python3.8/dist-packages/torch
    		04/27/2023 8:01 AM UTC
    sha256:4ff77931f3f53f399621f2df9f2c34f158c1e4bb3b58d2501d1337b53523c09bCOPY
    --chown=1000:1000dir:bf1c32fd3ef6d490b2efc47ee8d2038d8b49346d4db39a67df6c3903d5ccfcd8 in /usr/local/lib/python3.8/dist-packages/numpy
    		04/27/2023 8:01 AM UTC
    sha256:407e25a36be201d16a739ffb81009a43bc196fab8e84ea94116a0a2973b07f86COPY
    --chown=1000:1000dir:f3c2c20c90fd3d637fba1bcf5e633b1e331646c3bfd6cbcd8c659e0d2ab43ee8 in /usr/local/lib/python3.8/dist-packages/numba
    		04/27/2023 8:01 AM UTC
    sha256:3ed7a0d7cbdb97a011905f39ebb40492d0fe6e8a54fa04cc8dc25d48c96bbf03COPY
    --chown=1000:1000dir:44b1bcfb484d7a5b0dd769e0530d6e1a3c53f3fd8830e3467ef8ad75b613abe6 in backends/pytorch
    		04/27/2023 8:01 AM UTC
    sha256:992b53fa35e361b7e4d2c065702ca3417f072cd18c2985cb351a09f504a61bd0RUN
    pip install --no-cache-dir --no-deps torch torchmetrics &&
  pip install --no-cache-dir --upgrade pip &&
  pip install sympy &&
  rm -rf /usr/local/lib/python3.8/dist-packages/torch &&
  rm -rf /usr/local/lib/python3.8/dist-packages/caffe2
    		04/27/2023 8:01 AM UTC
    ...