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Operations

Use this page for operational folder hygiene, validation checks, and release/security workflows. Prerequisite: project dependencies installed in your active environment.

Artifact Directories

  • data/: prepared datasets, including data/meta.json for bin runs.
  • checkpoints/: training outputs (ckpt_last.pt, train_log.json).
  • outputs/: exported artifacts (hf_export/, gguf/, fine-tuning outputs).
  • runs/: optional experiment logs or external tracker exports (not auto-created by core scripts).

Note

The core training scripts write to checkpoints/ and outputs/. Keep those directories versioned in your run notes, but do not commit large artifacts.

Command(s)

Local quality checks:

python -m pytest -q
ruff check src scripts tests train.py generate.py demo_gradio.py --select E9,F63,F7,F82

Docs build checks:

python -m pip install -r docs/requirements.txt
python -m mkdocs build

Output Files / Artifacts Produced

  • Test and lint logs in terminal output
  • Built docs in site/ after mkdocs build
  • CI pipelines: .github/workflows/ci.yml and .github/workflows/docs.yml

Security and Release

Security reporting (see SECURITY.md):

  • Use GitHub Security Advisories for vulnerabilities
  • Include impact, affected components, and reproduction steps

Release flow (see RELEASE.md):

  1. Confirm CI is green.
  2. Run local validation commands.
  3. Update version and changelog.
  4. Tag and publish the release.

Common Errors