HomeToolsMCPHow It WorksStoriesPhilosophyArchitectureStar on GitHub
All Tools
W
MonitoringFreemium

WEIGHTS & BIASES

Experiment tracking, LLM tracing, and model registry for ML and AI teams

MIT

ABOUT

ML and LLM teams often scatter metrics, configs, prompts, traces, and artifacts across notebooks, scripts, dashboards, and ad hoc spreadsheets. Weights & Biases gives teams one system to log runs, compare experiments, version artifacts, trace LLM applications, and review results collaboratively so they can reproduce work, catch regressions, and decide which models or prompts actually improved.

INSTALL
pip install wandb

INTEGRATION GUIDE

1. Track training metrics, configs, and checkpoints across many model runs 2. Compare prompt, model, and parameter variants for LLM applications 3. Store versioned datasets, models, and artifacts with lineage metadata 4. Run hyperparameter sweeps and review results in one workspace 5. Trace LLM or agent calls and score outputs during evaluation workflows 6. Share dashboards, reports, and alerts with researchers and product teams

TAGS

experiment-trackingllm-observabilitymodel-registrysweepsmlopsevaluationsartifacts