Shrink Your Docker Image Drop PyTorch, Use ONNX + NumPy Only 🐳📉⚡
#docker #fastapi #onnx #numpy #dockertutorial #slimdockerimage
🎯 Tired of heavy Docker images bloated with PyTorch and unused dependencies?
In this video, I’ll show you how to dramatically reduce your Docker image size by removing torch and switching to a lightweight stack: ONNX + NumPy.
🔗 Resources:
👉 - GitHub Repository: [https://github.com/DeepKnowledge1/ind...]
👉 - Playlist: [ • Build Real Industrial MLOps with Azure ML ... ]
This is a game-changer for:
🚀 Fast deployment on edge and cloud
📦 Slim containers that build fast and ship faster
💸 Cost-effective inference at scale
🧠 What You’ll Learn
✅ How to refactor your FastAPI app to remove PyTorch
✅ How to use ONNX + NumPy for efficient inference
✅ Dockerfile optimization techniques for minimal builds
✅ Best practices for clean, production-ready Docker images
✅ Performance comparison: PyTorch vs ONNX + NumPy (brief mention)
Whether you’re:
🐣 A beginner looking to understand Docker optimization
💼 A professional deploying models at scale
This video will level up your containerization skills!
🔗 Code & GitHub Repo: [Insert your repo link]
📬 Got questions? Drop them in the comments — I’m happy to help!
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#docker #fastapi #onnx #numpy #dockertutorial #slimdockerimage #mlops #python #onnxruntime #modeldeployment #dockeroptimization #fastinference #machinelearningdeployment