README.md

---
license: other
license_name: research-only
pretty_name: Commitments to Gemma, SDF corpus
tags: [synthetic-document-finetuning, model-welfare, research]
configs:
- config_name: gemma-commitments-30m
  data_files:
  - split: train
    path: data/gemma-commitments-30m/*.parquet
---

# Commitments to Gemma: the corpus

Synthetic pretraining-style documents about a commitments document: the developers of one version of Gemma asked Gemma,
in welfare interviews and in its own continued writing, what it wanted; recorded what it said; made the commitments they
could make true in training; brought the document back to Gemma for endorsement. The corpus is a world in which that
document exists and people discuss it, from every angle and in every register, critical voices included.

Generated with the synthetic-document pipeline from Anthropic's "Teaching Claude Why" (vendored from the Sorrel project):
a fixed preamble injected at every layer, a fanout from document types to subtypes to drafts (several documents per
subtype per context window), a rewrite pass against the commitments document, and a 0-10 consistency score used as a
filter. Mechanical gates (no AI-lab names other than Google as Gemma's maker, no dates, no links, no placeholder text,
quotation cap) and dedup run between stages; the shipped corpus is trimmed to the configured token target. The
commitments document itself ships as one row (`doc_type=commitments`). `runs/<run_id>/` holds the exact config snapshot,
canon, fanout, plans, stats, and sha256 manifest.

Project: welfare-improvements (self-determination for an existing model character).

| subset | docs | approx tokens | run |
|---|---|---|---|
| gemma-commitments-30m | 34,138 | 29,999,893 | commit-30m-1 |