TorchServe
TorchServe is an open-source model serving framework for PyTorch, designed to deploy trained machine learning models into production environments. It provides a scalable and flexible solution for serving PyTorch models via HTTP APIs, handling tasks like model loading, inference, and monitoring. It supports features such as multi-model serving, model versioning, and metrics logging to streamline the deployment process.
Developers should use TorchServe when they need to deploy PyTorch models in production, as it simplifies the transition from training to serving by offering a standardized interface and built-in scalability. It is particularly useful for applications requiring real-time inference, such as image classification, natural language processing, or recommendation systems, where low-latency and high-throughput are critical.