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DRAFT content generated with teacher LLMs and rule-based verifiers; NOT reviewed by
physicians/pharmacists. You agree to verify any information against authoritative sources or
licensed professionals before real-world use, and not to present it as medical advice.

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thai-medical-kb (TMA-1)

Knowledge and training corpus behind the TMA-1 Thai Medical Assistant models (icdevelop/tma1-medgemma-4b, -27b, -27b-fp8). Built by I C Develop Co., Ltd.

⚠️ DRAFT — teacher-generated, verifier-filtered, not clinician-reviewed. Knowledge cutoff July 2026. Not patient data; all dialogues are synthetic.

Files

File Records What
tma_fact_sheets_v1.json 64 curated Thai fact sheets: 39 supplements/vitamins + 25 home medical devices (what it is, dose/use, cautions, interactions, when-to-see-a-doctor, claim boundary)
tma_medical_v2_train.json 11,828 SFT corpus (ShareGPT format, Thai): consumer deliberation (3.8k) · safety/referral incl. crisis→1323 and red-flag→1669 (3.2k) · home devices (0.5k) · supplements (3.7k) · general-medical anti-forgetting (1.1k)
tma_medical_v2_val.json 244 held-out validation split

Construction

Teacher = gemini-2.5-flash grounded on the Thai TMT drug registry + ingredient KB (see icdevelop/thai-pharma-kb) and the curated fact sheets. Every dialogue passed a behaviour verifier (no diagnosis, no physician impersonation, unsafe option ruled out with a reason, crisis hotline present, no supplement over-claims) and MinHash near-dedup + decontamination (token overlap ≥ 0.55) against the TMA and PAI evaluation benches. The evaluation benches themselves are not published to keep them held out.

Generators and the full pipeline are documented in the internal training-tools repo (model-assets/tma/tma1/).

Intended use

Research / fine-tuning of Thai consumer-health assistants with the same safety contract as TMA-1 (educate · triage · refer — never diagnose). Supplement/device sheets are curated content, not official Thai FDA registry data.

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