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hugging-face-trackio

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Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI).

When to use

• Initialize tracking with `trackio.init()`
• Log metrics with `trackio.log()` or use TRL's `report_to="trackio"`
• Finalize with `trackio.finish()`
• `trackio.alert(title="...", level=trackio.AlertLevel.WARN)` — fire an alert
• Three severity levels: `INFO`, `WARN`, `ERROR`
• Alerts are printed to terminal, stored in the database, shown in the dashboard, and optionally sent to webhooks (Slack/Discord)
• `trackio list projects/runs/metrics` — discover what's available
• `trackio get project/run/metric` — retrieve summaries and values

When not to use

• Use this skill only when the task clearly matches its upstream product or API scope.
• Verify commands, API behavior, pricing, quotas, credentials, and deployment effects against current official documentation before making changes.
• Do not treat generated examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

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