huggingface-trackio
Tracks and visualizes ML training experiments with Trackio: metric logging, alerts, real-time dashboards, Space syncing and CLI retrieval.
- Kind
- Skill
- Works with
- Claude Code
- Source
- Hugging Face Skills @ 25910b3d0ba3
- Path
- skills/huggingface-trackio/SKILL.md
- Jobs
- Testing, Debugging
- Topics
- Machine learning
Credit
- Made by
- huggingface
- Original
- github.com/huggingface/skills/blob/25910b3d0ba31a2ba102f901cd…
- License
- Apache-2.0
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
hf skills add huggingface-trackio
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/huggingface-trackio/ (the skill folder)
- 3 file(s) the skill refers to
- Runs scripts
- Yes
- shell block in the text
- Uses the network
- None found
- Needs secrets
- None found
- Source revision
- 25910b3d0ba3
- Licence
- Apache-2.0
- Last activity
- 30 Oct 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# Trackio - Experiment Tracking for ML Training Trackio is an experiment tracking library for logging and visualizing ML training metrics. It syncs to Hugging Face Spaces for real-time monitoring dashboards. ## Three Interfaces | Task | Interface | Reference | |------|-----------|-----------| | **Logging metrics** during training | Python API | [references/logging_metrics.md](references/logging_metrics.md) | | **Firing alerts** for training diagnostics | Python API | [references/alerts.md](references/alerts.md) | | **Retrieving metrics & alerts** after/during training | CLI | [references/retrieving_metrics.md](references/retrieving_metrics.md) | ## When to Use Each ### Python API → Logging Use `import trackio` in your training scripts to log metrics: - Initialize tracking with `trackio.init()` - Log metrics with `trackio.log()` or use TRL's `report_to="trackio"` - Finalize with `trackio.finish()` **Key concept**: For remote/cloud training, pass `space_id` — metrics sync to a Space dashboard so they persist after the instance terminates. Auto-created Spaces are **public by default** — pass `private=True` if the metrics should not be public. …