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 -
Wave 1: fix 8 failing tests + unblock Docker E2E + dep/doc debt
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Backlog-resolution Wave 1 (branch backlog/goal-resolution-2026-06). Bugs fixed: - B1 (P0): generate spikes/007 synthetic_session_with_error.jsonl fixture (never committed — .gitignore *.jsonl whitelisted the sibling but not this one) → the 8 failing test_trace_examples_adapter tests now pass. Added the missing .gitignore whitelist line. - B2 (P2): [dev] extra was un-installable on Apple Silicon (pulled Linux-only torchft-nightly). Dropped diloco from base [dev]; added [dev-full] for Linux. - B3 (P2): [serverless] extra now includes s3fs/boto3/kubernetes (needed for real S3 rendezvous + the EKSExecutor/SageMakerExecutor adapters). Newly unblocked: - D1 (…-245d): Docker substrate E2E — Docker now available on host; both gates (4-gate substrate inversion + cache-scrub-in-container) PASS. Long-standing "hardware-blocked" item closed. Doc/API debt: - B4: reconciled divergent test counts (115/176/210/232) to one canonical figure measured this session: 266 passed / 62 skipp…c11cf49
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Wave 12: close V1-V8 brief — GPU smoke, SDPO firing, real-trace e2e
Addresses cross-model review priority items 3, 4, 5, 9 — the ones that materially close the original V1-V8 brief. Wave 12 deliverables: 1. **Spike 002a-mini-gpu-smoke** (NEW directory) — closes "zero GPU evidence": - 50-step Qwen2.5-0.5B-Instruct training run on local RTX 5090 (sm_120, Blackwell), bf16, in 35 s wall-clock total - Loss 0.7354 → 0.00034 (99.95% reduction), all grads finite, peak VRAM 5.31 GB (well under ADR-001's 8 GB target), median 480 ms/step - Captures per-step memory + step-time + finite-grads in results/gpu_loss_curve.csv + results/gpu_verdict.json - ADR-001's local-5090 choice now empirically verified (vs ~3-5 min cold-start cycle estimated for Modal L4) - Resolves cross-model review item #4 2. **Spike 006-strict** (`tests/test_strict.py`) — closes the tautology critique: - test_alternating_batches_loss_decreases: 10 steps alternating between factorial + binary_search variants. Late-avg-loss < 50% × early-avg-loss. …d88715c -
Wave 10 — packaging: composer_replication is now pip-installable
Promotes the framework from "skeleton scattered across spike directories" to a proper installable Python package (closes vision-validation gap V4). What's new: pyproject.toml at repo root - Hatchling build backend - Python ≥3.10 - Core deps: torch≥2.0, transformers≥4.46 - Optional extras: replay (httpx), diloco (torchft-nightly), train (trl, peft, accelerate, datasets), dev (everything + pytest, ruff) - Project URLs point to the HF repo + Discussions composer_replication/ package (8 modules) - __init__.py re-exports the framework's public API: compose_loss, LossComponents, build_batch (Spike 006) generalized_jsd_loss (verified port of OPSD) ClaudeCodeIngester, IngestionStats, SYSTEM_PROMPT (Spike 007) TraceState, DPOPair, TeacherSpec, replay_trace, extract_dpo_pairs, DEFAULT_TEACHERS (Spike 001/005) ComposerReplicationTrainer (Spike 005, TRL subclass) make_diloco_outer_loop …ac05fbf