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: 534 Bytes
f16fa23 f00833d | 1 2 3 4 5 6 7 8 9 | # Wave 7–10 Final Review — Cross-model adversarial check
> **📦 Archived (2026-06-08).** This point-in-time wave review has been moved to
> [`docs/research/_archive/WAVE_7_10_FINAL_REVIEW.md`](_archive/WAVE_7_10_FINAL_REVIEW.md).
> It is preserved verbatim for provenance but is superseded by the current
> [`docs/METHODOLOGY.md`](../METHODOLOGY.md), [`BACKLOG.md`](../../BACKLOG.md), and
> [`docs/V1_V8_COVERAGE.md`](../V1_V8_COVERAGE.md). See
> [`docs/research/_archive/README.md`](_archive/README.md) for the archive index.
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