metadata
license: other
license_name: health-ai-developer-foundations
license_link: https://developers.google.com/health-ai-developer-foundations/terms
library_name: transformers
pipeline_tag: image-text-to-text
extra_gated_heading: Access MedGemma on Hugging Face
extra_gated_prompt: >-
To access MedGemma on Hugging Face, you're required to review and agree to
[Health AI Developer Foundation's terms of
use](https://developers.google.com/health-ai-developer-foundations/terms). To
do this, please ensure you're logged in to Hugging Face and click below.
Requests are processed immediately.
extra_gated_button_content: Acknowledge license
base_model: google/medgemma-27b-text-it
tags:
- medical
- clinical-reasoning
- thinking
- mlx
- mlx-my-repo
mlx-community/medgemma-27b-text-it-8bit
The Model mlx-community/medgemma-27b-text-it-8bit was converted to MLX format from google/medgemma-27b-text-it using mlx-lm version 0.24.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/medgemma-27b-text-it-8bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)