torchserve

What problem does it solve?

This Skill simplifies the deployment of PyTorch models into production-ready inference servers, handling packaging, scaling, and custom request processing.

Core Features & Use Cases

• Model Packaging: Creates self-contained .mar files for consistent deployment.
• Custom Handlers: Allows Python code for pre/post-processing and custom inference logic.
• Multi-GPU Scaling: Manages worker distribution across available GPUs for efficient load balancing.
• Use Case: Deploy a custom image classification model with specific pre-processing steps by packaging it with a custom handler and serving it via TorchServe's REST API.

Quick Start

Use the torchserve skill to package the model 'my_model.pt' with the handler 'my_handler.py' into a MAR file named 'my_model.mar'.