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Codeseys
/
composer-replication-framework

Reinforcement Learning
Transformers
English
post-training
distillation
agentic-coding
composer-2.5
cursor
kimi-k2
grpo
dapo
diloco
openenv
trl
verl
research
methodology
Model card Files Files and versions
xet
Community

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-framework / composer_replication /recipes
57.6 kB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
Codeseys's picture
Codeseys
Wave 15: 4-angle multi-model self-critique caught 2 math BLOCKERs in primary loss kernels; fixed against upstream byte-for-byte + GSM8K example + ergonomics
e5add15 6 days ago
  • monarch
    Wave 13: serverless DiLoCo + replaysim normalization + 3 distillation losses + PRIME-RL + Monarch 6 days ago
  • prime_rl
    Wave 15: 4-angle multi-model self-critique caught 2 math BLOCKERs in primary loss kernels; fixed against upstream byte-for-byte + GSM8K example + ergonomics 6 days ago
  • replaysim
    Wave 14: close every Wave 13 review finding + 4 documentation files; Wave 14b: real PRIME-RL parity + multi-process DiLoCo convergence 6 days ago