How to Serve a PyTorch Model with FastAPI: A Complete Guide

1. 1Install FastAPI and PyTorch using pip
2. 2Build a PyTorch model and save it to a file
3. 3Create a FastAPI app and define a route for model inference
4. 4Load the PyTorch model in the FastAPI app and define a prediction function
5. 5Test the API using a tool like curl or Postman to verify model deployment

Data scientists and software engineers can benefit from this guide to deploy PyTorch models efficiently

💡 FastAPI provides a lightweight and efficient way to serve PyTorch models

🚀 Deploy PyTorch models with FastAPI for scalable ML serving