medgemma:4b

199 Downloads Updated 6 hours ago

MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension.

vision 4b 27b

ollama run medgemma:4b

curl http://localhost:11434/api/chat \
  -d '{
    "model": "medgemma:4b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='medgemma:4b',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'medgemma:4b',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Details

Updated 6 hours ago

6 hours ago

9fe4e9a6c9bd · 3.3GB ·

model

archgemma3

parameters4.3B

quantizationQ4_K_M

3.3GB

template

{{- range $i, $_ := .Messages }} {{- $last := eq (len (slice $.Messages $i)) 1 }} {{- if eq .Role "u

394B

license

# Health AI Developer Foundations Terms of Use Last modified: November 15, 2024 By using, reproducin

12kB

params

{ "stop": [ "<end_of_turn>" ] }

37B

Readme

MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension. Developers can use MedGemma to accelerate building healthcare-based AI applications. MedGemma is available in 4B and 27B versions.

Both MedGemma multimodal versions utilize a SigLIP image encoder that has been specifically pre-trained on a variety of de-identified medical data, including chest X-rays, dermatology images, ophthalmology images, and histopathology slides. Their LLM components are trained on a diverse set of medical data, including medical text, medical question-answer pairs, FHIR-based electronic health record data (27B multimodal only), radiology images, histopathology patches, ophthalmology images, and dermatology images.

Reference

Model card