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Procedural multi-step integer chains with boxed answers; uses ManagedServer and math_verify for scoring. No external dataset required. Made-with: Cursor
23 lines
889 B
Markdown
23 lines
889 B
Markdown
# Arithmetic Chain
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Self-contained RL environment: procedurally generated multi-step integer problems (add / subtract / multiply from a starting value). The model must answer with `\boxed{integer}`; rewards use the same `math_verify` path as GSM8K.
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**No Hugging Face dataset** — training items are sampled on the fly.
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## Run (serve)
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From the repo root, with Atropos API and an OpenAI-compatible inference server configured in `config_init` or via CLI overrides:
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```bash
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python environments/community/arithmetic_chain/arithmetic_chain_server.py serve --slurm false
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```
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## Process (debug rollouts)
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```bash
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python environments/community/arithmetic_chain/arithmetic_chain_server.py process \
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--env.data_path_to_save_groups rollouts.jsonl \
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--slurm false
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```
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Uses `ManagedServer` for token/logprob tracking (compatible with trainers that expect Atropos’ standard scored groups).
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