Reinforcement Learning
Transformers
English
post-training
distillation
agentic-coding
composer-2.5
cursor
kimi-k2
grpo
dapo
diloco
openenv
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research
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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.ingestion — trace-source adapters. | |
| v0.1: Claude Code session JSONL. | |
| v0.2 candidates: OpenHands trajectories, SWE-smith-trajectories. | |
| Per docs/adrs/ADR-002-trace-source.md. | |
| """ | |
| from __future__ import annotations | |
| from composer_replication.ingestion.claude_code import ( | |
| SYSTEM_PROMPT, | |
| ClaudeCodeIngester, | |
| IngestionStats, | |
| ) | |
| from composer_replication.ingestion.trace_examples import ( | |
| TOOL_ERROR_TAG, | |
| claude_states_to_trace_examples, | |
| default_classify_error, | |
| ) | |
| __all__ = [ | |
| "ClaudeCodeIngester", | |
| "IngestionStats", | |
| "SYSTEM_PROMPT", | |
| "TOOL_ERROR_TAG", | |
| "claude_states_to_trace_examples", | |
| "default_classify_error", | |
| ] | |