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PyTorch/Recommendation/DLRM/triton/README.md

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@@ -25,7 +25,7 @@ The very first step of deployment is to acquire trained checkpoint and model con
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checkpoint. Default model configuration are stored inside `dlrm/config` directory.
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**Currently, our implementation only supports TorchScript deployment for models that fit into the memory of a single GPU.**
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You can read more about training DLRM models on different dataset configurations based on frequency threshold in the preprocessing step in [README](https://gitlab-master.nvidia.com/dl/JoC/dlrm_pyt#preprocess-with-spark).
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You can read more about training DLRM models on different dataset configurations based on frequency threshold in the preprocessing step in [README](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Recommendation/DLRM/README.md#preprocess-with-spark).
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#### Inference container
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