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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Codeseys/composer-replication-framework", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Wave 2: 4 new modules (kill-switch, EKS/SageMaker executors, DockerSandbox) + B4/B7 completion
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Built by the parallel execution team (worktree-isolated), integrated + tested here. New modules (all CPU-testable via mock/lazy-import; optional deps gated): - composer_replication/safety/ — HeldOutGuard run-level collapse kill-switch (held-out-declines-while-reward-rises streak + KL-to-init hard-stop 0.08 + proxy-real hacking-gap; EMA-denoised, latched-fire, CollapseStopError). The documented #2 safeguard for the self-evolving flywheel. 23 tests. - composer_replication/diloco/serverless/eks.py — EKSExecutor satisfying the ServerlessExecutor Protocol via a SINGLE Kubernetes Indexed Job → N rank-ordered ReplicaHandles, gang-cancel (Background propagation), REPLICA_RANK via the downward API, S3 rendezvous (IRSA). 28 tests (mock BatchV1/CoreV1). - composer_replication/diloco/serverless/sagemaker.py — SageMakerExecutor (boto3 create_training_job, same S3 rendezvous, status mapping). +13-test module written during integration (the build agent shipped it test-less). - compos…7a55e1e
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Wave 13: serverless DiLoCo + replaysim normalization + 3 distillation losses + PRIME-RL + Monarch
Expanded the brief mid-deep-work-loop to address the user's request for serverless training-system support, replaysim dataset normalization, deeper self-distillation paper coverage, and Meta's PyTorch agentic stack tie-ins. NEW MODULES (35 tests passing): - composer_replication.distillation: SimPO (arXiv:2405.14734), TAID (arXiv:2501.16937), Entropy-Aware OPD (ICLR 2026 spotlight). 17 unit tests covering scalar/differentiable/scheduler-monotonicity and boundary-condition correctness against paper formulas. - composer_replication.diloco.serverless: ServerlessExecutor Protocol + ObjectStoreAllReduce (fsspec-backed; works with file:// + s3:// + hf:// + gs:// + az://) + LocalProcessExecutor (working) + ModalExecutor / HFJobsExecutor (skeletons, raise NotImplementedError). 9 tests including 3 multi-process tests pinning the allreduce barrier with mean-of-{0,1,2}=1 + mean-of-{0,100,200}=100 across two consecutive rounds. - composer_replication.replaysim: data-juicer adapte…b266c31