Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Modify or upstream behavior in a named Grug/Grugformer experiment variant.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Grug is intentionally template-first: the canonical edit surface lives in experiments/grug/base/, not in a shared levanter.grug trainer stack.
This skill covers two steps: trying a change in an experiment copy, and upstreaming it into the base template when it proves out.
Do not use this skill to run an existing variant, change launch-only configuration, or add a bounded operational diagnostic. Use the variant README and launcher controls for those tasks.
experiments/grug/base/ — model.py, train.py, launch.py.experiments/grug/<variant>/ — copy from base and modify locally (e.g. MoE).experiments/speedrun/... — useful for exploration, not canonical.Keep each pass scoped to one bucket:
experiments/grug/base to a new variant directory.Update docs/reports/grug-archive.md with: path, origin (base, moe, or another source variant), commit SHA (when known), purpose, status (active, superseded, deleted), and diff link (prefer the CI-posted PR comment link; fallback to local report path).
For PRs that add a new experiments/grug/<variant>/, CI posts a visual diff comment automatically — copy that link into the archive entry.
For a local fallback, generate the diff report manually and link the report in the archive entry:
uv run python scripts/ci/grug_dir_diff.py \
experiments/grug/base \
experiments/grug/<variant> \
--out /tmp/grug-diff
Port the successful change back into experiments/grug/base/model.py, train.py, and launch.py. Keep it grug-style:
init + __call__docs/references/hbm-optimization.md before bespoke memory hacksAfter upstreaming, delete superseded experiment code; keep only the archive trail in docs/reports/grug-archive.md.
./infra/pre-commit.py --all-files
uv run pytest tests/test_grug_variant_contracts.py
Add focused tests for any behavior changes.
This workflow is inspired by modded-nanogpt: iterate quickly in copy-paste experiments, then upstream only what stays simple and useful.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
日本語の概要は準備中です。原文の説明を表示しています。
Implement a fully specified request for a GCP IAM resource grant or Cloud Run IAP viewer in marin-iac.
日本語の概要は準備中です。原文の説明を表示しています。
Add or change a named Pallas/Mosaic kernel, including its reference implementation, correctness tests, wrapper, or requested tuning.
日本語の概要は準備中です。原文の説明を表示しています。
Archive explicitly named legacy experiment files by publishing a dated tag and canonical issue breadcrumbs.
日本語の概要は準備中です。原文の説明を表示しています。
Launch or continuously monitor a specified Zephyr pipeline on Iris only when asked to babysit it; restart only after explicit approval.
日本語の概要は準備中です。原文の説明を表示しています。