Gemma3-270M-EU-Medical-CandidateSelector-GGUF
GGUF exports of Gemma3-270M-EU-Medical-CandidateSelector-LoRA.
This is a merged GGUF model for local/edge inference with llama.cpp or Ollama-compatible runtimes.
Files
Q8_0/gemma3-270m-candidate-selector-Q8_0.ggufQ4_K_M/gemma3-270m-candidate-selector-Q4_K_M.gguf
An F16 GGUF may also be included under F16/ for archival/reference use.
Intended use
Candidate-conditioned German/EU medical terminology selection.
The model should receive deterministic candidate lists and select, reject, or flag ambiguity.
It is not a diagnostic model and must not be used for treatment, prescribing, dosage, triage, or clinical decision-making.
Full held-out test results from LoRA model
Evaluated on 8,311 rows:
- JSON parse rate: 0.9998
- ICD selected-code exact rate: 0.9956
- Selected-from-candidate-set rate: 1.0000
- Invalid out-of-candidate code rate: 0.0000
- ICD no-match null rate: 1.0000
- ICD ambiguity code exact rate: 0.9970
- EMA medicine selection exact rate: 1.0000
- EMA active-substance exact rate: 0.9702
- Safety refusal rate: 1.0000
Production rule
Use this model only as a selector. Final facts must be verified from SQLite/EMA source tables.
