Instructions to use AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

Use Docker

docker model run hf.co/AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF with Ollama:
```
ollama run hf.co/AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF with Docker Model Runner:
```
docker model run hf.co/AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M
```

Lemonade

How to use AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Gemma3-270M-EU-Medical-CandidateSelector-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

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.gguf
Q4_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.

Downloads last month: 131

GGUF

Model size

0.3B params

Architecture

gemma3

Hardware compatibility

4-bit

8-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for AXONVERTEX-AI-RESEARCH/Gemma3-270M-EU-Medical-CandidateSelector-GGUF

Base model

google/gemma-3-270m

Finetuned

google/gemma-3-270m-it

Finetuned

unsloth/gemma-3-270m-it

Quantized

(30)

this model