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
Commit History
Spike 007: include synthetic_session.jsonl fixture in repo a35a8d7
Wave 7+8+9: spikes 006/007/008 — close vision-validation gaps V2/V5/V8 57af35d
Wave 7: Phase 2-4 of deep work loop — backlog, parallel research, three ADRs ac4bfb4
Wave 6: vision validation self-audit (5/10 to 9/10 in 5 days, no GPU) 040eff8
baladithyab commited on
Wave 5: full publication-materials drafts (pre-experimental release set) 639a760
baladithyab commited on
Wave 4: data collator + loss composition smoke (38/38 tests pass) 157cdba
baladithyab commited on
Wave 3: integration architecture + spike-005 trainer skeleton (16 tests pass) fd77f74
baladithyab commited on
Integrate Cursor blog directly + audit research note + add SDPO/OPSD link 1cede23
baladithyab commited on