functiongemma-270m-it-bf16/README.md

license, tags, pipeline_tag, library_name, extra_gated_heading, extra_gated_prompt, extra_gated_button_content, base_model

license	tags	pipeline_tag	library_name	extra_gated_heading	extra_gated_prompt	extra_gated_button_content	base_model
gemma	gemma3 gemma google functiongemma mlx	text-generation	mlx	Access Gemma on Hugging Face	To access FunctionGemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.	Acknowledge license	google/functiongemma-270m-it

mlx-community/functiongemma-270m-it-bf16

This model mlx-community/functiongemma-270m-it-bf16 was converted to MLX format from google/functiongemma-270m-it using mlx-lm version 0.28.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/functiongemma-270m-it-bf16")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)