Reinforcement Learning
Transformers
English
post-training
distillation
agentic-coding
composer-2.5
cursor
kimi-k2
grpo
dapo
diloco
openenv
trl
verl
research
methodology
Instructions to use Codeseys/composer-replication-framework with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Codeseys/composer-replication-framework with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Codeseys/composer-replication-framework", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| # docs/_archive — historical, point-in-time artifacts | |
| This directory holds **non-research** documents that captured the state of the | |
| project at a specific moment (wave logs, dated cross-family review bundles). | |
| They are preserved **verbatim for provenance** and are **not** maintained as | |
| current truth. | |
| > **What's current instead.** For the live state of the framework, read | |
| > [`docs/OVERVIEW.md`](../OVERVIEW.md), [`README.md`](../../README.md), | |
| > [`BACKLOG.md`](../../BACKLOG.md), [`docs/METHODOLOGY.md`](../METHODOLOGY.md), | |
| > [`docs/V1_V8_COVERAGE.md`](../V1_V8_COVERAGE.md), and the accepted ADRs under | |
| > [`docs/adrs/`](../adrs/README.md). Where an archived doc and a current doc | |
| > disagree, the current doc wins. | |
| Each archived file's original path still contains a one-line **redirect stub** so | |
| that older prose references (including those baked into immutable accepted ADRs) | |
| keep resolving. | |
| ## Contents | |
| | Archived file | Original path | What it is | Superseded by | | |
| |---|---|---|---| | |
| | [`WAVE_COMPOSER_DATAGEN_RL_2026-05-29.md`](WAVE_COMPOSER_DATAGEN_RL_2026-05-29.md) | `docs/WAVE_COMPOSER_DATAGEN_RL_2026-05-29.md` | Wave log: Composer datagen + targeted-RL textual-feedback work, 2026-05-29 | ADR-008, ADR-009, ADR-010, ADR-014; `BACKLOG.md` | | |
| | [`DEEP_WORK_LOOP_LOG.md`](DEEP_WORK_LOOP_LOG.md) | `docs/DEEP_WORK_LOOP_LOG.md` | Running log of deep-work-loop sessions | `docs/METHODOLOGY.md`; `BACKLOG.md` | | |
| | [`reviews/cross-family-adr-008-009-010-2026-05-29/`](reviews/cross-family-adr-008-009-010-2026-05-29/) | `docs/reviews/cross-family-adr-008-009-010-2026-05-29/` | 5-family adversarial review of ADR-008/009/010 (SYNTHESIS + 4 per-model reviews) | ADR-008 / ADR-012 acceptance records | | |
| | [`reviews/final-verify-deep-work-2026-05-29/`](reviews/final-verify-deep-work-2026-05-29/) | `docs/reviews/final-verify-deep-work-2026-05-29/` | Phase-8 final cross-family verify (SYNTHESIS + per-model verifies) | accepted ADRs; `BACKLOG.md` | | |
| ## Why archive instead of delete | |
| These documents record *how the decisions were reached* — the adversarial | |
| findings, the wave-by-wave reasoning, the cross-model disagreements. That | |
| provenance is valuable for anyone auditing the framework's claims, and the | |
| accepted ADRs cite these paths by name. Deleting them would orphan those | |
| citations and erase the audit trail. Archiving keeps the trail intact while | |
| making clear they are snapshots, not the live spec. | |
| > Research-flavored point-in-time reviews (the `WAVE_*_FINAL_REVIEW.md` | |
| > cross-model audits and the Wave-16 recon audit) live in the sibling | |
| > [`docs/research/_archive/`](../research/_archive/README.md) instead. | |