labml.ai

Monitors ML model training and hardware from mobile with easy experiment tracking. It captures metrics, hyperparameters, git commit details, console prints, and system info like hardware usage automatically. The core library and most features stay open-source and free, with optional hosted views possibly having extras. Primarily built for PyTorch, but the tracker can adapt to other frameworks with manual logging. Dashboard access uses local servers or secure hosted options; always use authentication when exposing remotely. Share the dashboard URL or run a shared server for team access. Core tracking and local dashboard work offline; mobile access needs a reachable server.