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Run PyTorch and ONNX models on Triton Inference Server without GPU

This article details how to run both PyTorch and ONNX models simultaneously on a single inference server using NVIDIA's Triton Inference Server. The process is demonstrated on a local Mac environment without requiring a GPU, highlighting the flexibility and accessibility of the setup for MLOps practices. AI

IMPACT Enables efficient deployment of diverse AI models on a single server, reducing infrastructure needs and simplifying MLOps workflows.

RANK_REASON The article describes a technical how-to guide for deploying existing models on a specific inference server, which falls under tooling.

Read on Medium — MLOps tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Run PyTorch and ONNX models on Triton Inference Server without GPU

COVERAGE [2]

  1. Medium — MLOps tag TIER_1 English(EN) · Shikha Singh ·

    Running a PyTorch Model on Triton (alongside onnx) — MLOPs Part 2

    <div class="medium-feed-item"><p class="medium-feed-snippet">Running two models from two different frameworks on a single inference server, no GPU required.</p><p class="medium-feed-link"><a href="https://medium.com/@shiqs90/running-a-pytorch-model-on-triton-alongside-onnx-mlops-…

  2. Medium — MLOps tag TIER_1 English(EN) · Shikha Singh ·

    Running a PyTorch Model on Triton (alongside onnx) — MLOPs Part 2

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/the-ai-affair/running-a-pytorch-model-on-triton-alongside-onnx-mlops-part-2-817ea2b5530a?source=rss------mlops-5"><img src="https://cdn-images-1.medium.com/max/1536/1*P8ZqWGMIyDtefeAE7yKEsg.png…