huggingface-trackio

Instrument, monitor, compare, and diagnose machine-learning experiments with Trackio metrics, alerts, dashboards, and structured exports.

Skill by metaspartan

IndexedMIT★ 32

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/metaspartan-huggingface-trackio

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About

Instrument, monitor, compare, and diagnose machine-learning experiments with Trackio metrics, alerts, dashboards, and structured exports.

Use cases: ml

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

Tools: No tools found
Secrets: None asked for
Install scripts: None found

Network hosts it talks to 1

codeload.github.com · found in install command

Files it touches

~/.claude/skills/huggingface-trackio

What's inside

Skill name: huggingface-trackio
Description: Instrument, monitor, compare, and diagnose machine-learning experiments with Trackio metrics, alerts, dashboards, and structured exports.
License: MIT
Instructions: 31 lines in SKILL.md · view on GitHub

Files (1)

SKILL.md

SKILL.md (first lines)

# Hugging Face Trackio

Use Trackio to make training state observable and reproducible.

## Instrumentation

```python
import trackio

trackio.init(project="project-name", config={"learning_rate": 0.0001})
trackio.log({"loss": 0.1, "learning_rate": 0.0001, "step": 1})
trackio.finish()
```

Use `report_to="trackio"` when the selected trainer supports it. For remote training, configure a durable Space or other supported synchronization target so metrics survive the job.

## Required signals

- train and evaluation loss
- task-specific evaluation metrics
- learning rate and step or epoch
- examples or tokens processed per second
- GPU memory or system utilization when available
- configuration, model revision, dataset revision, and seed
- alerts for NaN/Inf values, loss divergence, stalled progress, and failed persistence

Use structured CLI output when retrieving metrics for an agent. Compare runs only after verifying that their model, data, method, and evaluation settings are compatible.

Creating or changing a public tracking Space, webhook, or external alert destination transmits data. Confirm the destination and the metrics being sent before enabling it, and never log secrets or raw sensitive examples.

From metaspartan/cybara, MIT.

Signals

Stars: 32
Forks: 9
Open issues: 0
Last commit (this folder): Jul 30, 2026 (3 months ago)
Last release: Oct 24, 2026 (5 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License: MIT
Repository: github.com/metaspartan/cybara
Website: cybara.ai
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: GitHub github-graphql

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huggingface-trackio skill. Agent Mart. https://agentmart.dev/skills/metaspartan-huggingface-trackio (last updated 2026-10-24)