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
File size: 491 Bytes
b266c31 f00833d | 1 2 3 4 5 6 7 8 9 | # Wave 13 Adversarial Cross-Model Review
> **📦 Archived (2026-06-08).** This point-in-time wave review has been moved to
> [`docs/research/_archive/WAVE_13_FINAL_REVIEW.md`](_archive/WAVE_13_FINAL_REVIEW.md).
> It is preserved verbatim for provenance (ADR-007 cites its "Finding 2") but is
> superseded by the current [`docs/METHODOLOGY.md`](../METHODOLOGY.md) and
> [`BACKLOG.md`](../../BACKLOG.md). See
> [`docs/research/_archive/README.md`](_archive/README.md) for the archive index.
|