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: 517 Bytes
ac05fbf c11cf49 ac05fbf c11cf49 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | """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",
]
|