MLOps
Deploying inference models with Docker & GPU
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Packaging model serving into containers and managing GPU resources across multiple replicas.
Overview
This article shows how to package an open-weight model (Llama 3, Mistral) into a container for inference serving.
Packaging the container
Base image ships with a CUDA runtime, with environment variables selecting the model and inference parameters.
Managing GPU resources
Sharing a GPU across multiple replicas requires careful memory-limit configuration to avoid out-of-memory errors.
Tags
mlopsgpu
AI
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