Datasets:
loop-qwen-v8 SFT dataset (Gemini insulin-control distillation)
8,222 chat-format examples used to SFT loop-qwen-v8 (Qwen3-4B insulin
controller distilled from Gemini-3-flash-preview). Each example is a closed-loop
dosing decision.
Format (JSONL, one chat per line)
- system: controller spec (IOB-aware, Chain-of-Draft reason-before-act)
- user: patient metadata (age, weight, TDD, CF, IC, basal) + 6h history of CGM / insulin / carbs, as JSON
- assistant: JSON
{"reasoning": "...", "basal_chunk": [5], "bolus_chunk": [5]}(reason-first, then the 5-step basal U/hr + bolus U action)
Composition
- Gemini (rules-off + IOB + CoD) demonstrations on the 21 training patients (held-out 9 excluded — leakage guard).
- Multi-seed meals (seeds 42/7/13/21) — the key ingredient that let the 4B student reach teacher parity without dosing oscillation.
- Built via
gen_teacher_data.py->audit_to_sft.py(see the loop-gpt repo).
Companion model
jxx123/loop-qwen-v8 - the 2.5 GB Q4 model trained on this data (held-out-9: TIR 72.4% vs Gemini 73.5%, survival 9/9).
Research artifact
Simulation (simglucose) only. Not a medical device; do not use for real insulin dosing.
- Downloads last month
- 13