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
| """composer_replication.trainer — TRL GRPOTrainer subclass + data collator. | |
| Per docs/INTEGRATION_ARCHITECTURE.md § "Recipe A". | |
| Per docs/adrs/ADR-003 (also wraps DiLoCo when training distributed). | |
| """ | |
| from __future__ import annotations | |
| from composer_replication.trainer.composer_trainer import ( | |
| PO_OBJECTIVES, | |
| ComposerReplicationTrainer, | |
| make_dr_grpo_config, | |
| make_po_config, | |
| ) | |
| __all__ = [ | |
| "ComposerReplicationTrainer", | |
| "make_dr_grpo_config", | |
| "make_po_config", | |
| "PO_OBJECTIVES", | |
| ] | |