hugging-face-trackio
Trackio is an experiment tracking library that logs ML training metrics via a Python API and retrieves them through a CLI, with real-time dashboard visualization synced to Hugging Face Spaces. Use the Python API to instrument training scripts with metric logging, and use the CLI commands to query, analyze, and export logged metrics in JSON format for automation workflows.
git clone --depth 1 https://github.com/patchy631/ai-engineering-hub /tmp/hugging-face-trackio && cp -r /tmp/hugging-face-trackio/hugging-face-skills/skills/hugging-face-trackio ~/.claude/skills/hugging-face-trackioSKILL.md
# 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.
## Two Interfaces
| Task | Interface | Reference |
|------|-----------|-----------|
| **Logging metrics** during training | Python API | [references/logging_metrics.md](references/logging_metrics.md) |
| **Retrieving metrics** 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.
→ See [references/logging_metrics.md](references/logging_metrics.md) for setup, TRL integration, and configuration options.
### CLI → Retrieving
Use the `trackio` command to query logged metrics:
- `trackio list projects/runs/metrics` — discover what's available
- `trackio get project/run/metric` — retrieve summaries and values
- `trackio show` — launch the dashboard
- `trackio sync` — sync to HF Space
**Key concept**: Add `--json` for programmatic output suitable for automation and LLM agents.
→ See [references/retrieving_metrics.md](references/retrieving_metrics.md) for all commands, workflows, and JSON output formats.
## Minimal Logging Setup
```python
import trackio
trackio.init(project="my-project", space_id="username/trackio")
trackio.log({"loss": 0.1, "accuracy": 0.9})
trackio.log({"loss": 0.09, "accuracy": 0.91})
trackio.finish()
```
### Minimal Retrieval
```bash
trackio list projects --json
trackio get metric --project my-project --run my-run --metric loss --json
```>
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