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: 457 Bytes
d9dd3a5 f00833d | 1 2 3 4 5 6 7 8 | # Wave 14 Adversarial Cross-Model Review
> **📦 Archived (2026-06-08).** This point-in-time wave review has been moved to
> [`docs/research/_archive/WAVE_14_FINAL_REVIEW.md`](_archive/WAVE_14_FINAL_REVIEW.md).
> It is preserved verbatim for provenance but is superseded by the current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.
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