TorchServe is a flexible and easy-to-use tool for serving PyTorch models. It provides capabilities for packaging models, scaling workers based on hardware availability, and managing multiple model versions via a REST/gRPC API.
Use TorchServe when you need a production-ready inference server that handles multi-GPU load balancing, request batching, and custom preprocessing/postprocessing logic via Python handlers.
Model serving engine for PyTorch. Focuses on MAR packaging, custom handlers for preprocessing/inference, and management of multi-GPU worker scaling. (torchserve, mar-file, handler, basehandler, model-archiver, inference-api) Source: cuba6112/skillfactory.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/cuba6112/skillfactory --skill torchserve Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw