Gemma-3 Endocrinology Scenario-Based MCQ Models (20 Variants)
This collection contains 20 instruction-tuned Gemma-3 variants (270M–27B) optimized for endocrinology scenario-based MCQs and clinical Q&A. Variants are provided as LoRA adapters, merged FP16, and GGUF builds (FP16 and Q4_K_M) for flexible deployment from research servers to local/offline inference.
What the models can do
All variants are designed for three primary inference modes:
- Scenario MCQ Answering (with explanation): Provide the single best answer (A/B/C/D) and explain the reasoning.
- Scenario MCQ Generation: Generate a full clinical MCQ (stem + options + correct answer + brief explanation).
- General Endocrinology Q&A: Provide concise, structured answers to general endocrinology questions.
Important: These models are intended for educational and research purposes only and must not be used for clinical decision-making.
Dataset provenance and medical review
The dataset was designed and prepared by Professor _Saeed Awad M. Alqahtani _ (Taibah University, Saudi Arabia) and reviewed and approved by three licensed medical doctors:
- Two consultant endocrinologists
- One general medical doctor
Model variants in this collection:
270M (4 variants)
- HAJERI/gemma-3-270m-endocrinology-scenario-mcq-it-lora
- HAJERI/gemma-3-270m-endocrinology-scenario-mcq-it-merged-fp16
- HAJERI/gemma-3-270m-endocrinology-scenario-mcq-it-fp16-gguf
- HAJERI/gemma-3-270m-endocrinology-scenario-mcq-it-Q4_K_M-gguf
1B (4 variants)
- HAJERI/gemma-3-1b-endocrinology-scenario-mcq-it-lora
- HAJERI/gemma-3-1b-endocrinology-scenario-mcq-it-merged-fp16
- HAJERI/gemma-3-1b-endocrinology-scenario-mcq-it-fp16-gguf
- HAJERI/gemma-3-1b-endocrinology-scenario-mcq-it-Q4_K_M-gguf
4B (4 variants)
- HAJERI/gemma-3-4b-endocrinology-scenario-mcq-it-lora
- HAJERI/gemma-3-4b-endocrinology-scenario-mcq-it-merged-fp16
- HAJERI/gemma-3-4b-endocrinology-scenario-mcq-it-fp16-gguf
- HAJERI/gemma-3-4b-endocrinology-scenario-mcq-it-Q4_K_M-gguf
12B (4 variants)
- HAJERI/gemma-3-12b-endocrinology-scenario-mcq-it-lora
- HAJERI/gemma-3-12b-endocrinology-scenario-mcq-it-merged-fp16
- HAJERI/gemma-3-12b-endocrinology-scenario-mcq-it-fp16-gguf
- HAJERI/gemma-3-12b-endocrinology-scenario-mcq-it-Q4_K_M-gguf
27B (4 variants)
- HAJERI/gemma-3-27b-endocrinology-scenario-mcq-it-lora
- HAJERI/gemma-3-27b-endocrinology-scenario-mcq-it-merged-fp16
- HAJERI/gemma-3-27b-endocrinology-scenario-mcq-it-fp16-gguf
- HAJERI/gemma-3-27b-endocrinology-scenario-mcq-it-Q4_K_M-gguf
How to choose the right variant
Pick by deployment format
-
-lora: best if you want to keep the base model separate and apply adapters (research workflows, experimentation).
-
-merged-fp16: best for GPU inference with a standard Transformers pipeline (higher quality, higher VRAM).
-
-fp16-gguf: best for llama.cpp inference with high quality (larger RAM/VRAM than quantized).
-
-Q4_K_M-gguf: best for fast, memory-efficient local inference (most users on laptops/desktops).
Pick by model size
- 270M / 1B: fastest, lowest resource, good for lightweight education and constrained hardware.
- 4B: strong balance of speed and reasoning.
- 12B: best general quality/medical reasoning balance for many users.
- 27B: highest reasoning quality (requires more compute).
Prompt templates (the 3 modes)
Mode 1 — MCQ Answer + Explanation
You are an expert endocrinologist.
Clinical scenario:
A 32-year-old woman presents with weight loss, heat intolerance, and palpitations.
Labs: suppressed TSH and elevated free T4.
Options:
A. Subacute thyroiditis
B. Graves disease
C. Hashimoto thyroiditis
D. Pituitary adenoma
Instructions:
- Choose the single best answer.
- Explain the reasoning.
Mode 2 — Generate a full MCQ
You are an expert endocrinologist.
Create a clinical multiple-choice question on diabetic ketoacidosis suitable for
final-year medical students.
Include:
- A clinical scenario
- Four answer options
- The correct answer
- A brief explanation
Mode 3 — General Endocrinology Q&A
You are an expert endocrinologist.
Question:
Explain the mechanism of action of metformin.
Inference examples
A) GGUF inference with llama.cpp (recommended for GGUF models)
Example (Q4_K_M GGUF):
./main
-m gemma-3-12b-endocrinology-scenario-mcq-it-Q4_K_M.gguf
-p "You are an expert endocrinologist. Explain the pathophysiology of diabetic ketoacidosis."
-n 400
--temp 0.7
Example (FP16 GGUF):
./main
-m gemma-3-12b-endocrinology-scenario-mcq-it-fp16.gguf
-p "You are an expert endocrinologist. Create a clinical MCQ on DKA with 4 options and explanation."
-n 500
--temp 0.7
B) Merged FP16 inference with Transformers (for -merged-fp16)
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "HAJERI/gemma-3-12b-endocrinology-scenario-mcq-it-merged-fp16"
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
prompt = """You are an expert endocrinologist.
Question:
Explain the mechanism of action of metformin.
"""
inputs = tok(prompt, return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=350, temperature=0.7, do_sample=True)
print(tok.decode(out[0], skip_special_tokens=True))
Safety note
These models can generate clinically plausible text. Always apply:
-
Human expert review
-
Educational context only
-
No patient-specific decisions
Compute acknowledgement
Compute resources (NVIDIA A100 80GB) were supplied by the National eLearning Center (NeLC), Saudi Arabia, as part of the AI Sandbox in Digital Learning initiative.
Authors and contact
Model author: Professor Saeed Awad M. Alqahtani
Affiliation: Taibah University, Saudi Arabia
For academic, educational, or research inquiries: please open an issue on the relevant model repository.
