张宗平 8aeddebce9 test(m4): instruct_check unit tests + unbuffered training scripts
- tests/test_instruct_check.py: cover load_by_category (bucketing/cap/seed
  determinism/short-pool/blank-line) and _forecast_list (nested/flat/
  dict/garbage). 8 tests pass.
- train_stage{1,2}.sh: export PYTHONPATH=src + PYTHONUNBUFFERED=1 so future
  background runs stream logs live (current stage2 run is block-buffered).
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tsmm

Time-series as a Modality — an experimental, single-GPU multimodal model that treats multivariate time series as an independent modality, jointly injected into a small LLM (Qwen2.5-0.5B) for time-series question answering and reasoning (ChatTS route).

Status

M1 (data pipeline) under construction. See docs/superpowers/specs/2026-06-29-ts-as-modality-design.md for the design and docs/superpowers/plans/2026-06-29-ts-as-modality-plan.md for the task plan.

Layout

src/tsmm/   package (data, model, train, eval)
configs/    training / data configs
scripts/    offline generation & training entrypoints
tests/      pytest suite
data/       generated datasets (gitignored)
checkpoints/ model checkpoints (gitignored)

Install (dev)

python3 -m venv .venv
. .venv/bin/activate
pip install -e .            # full deps (incl. torch/transformers/peft/...)
# M1-only lightweight install:
pip install numpy tqdm pyyaml pytest && pip install -e . --no-deps
S
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