README.md

metadata

license: gemma
pipeline_tag: text-generation
library_name: mlx
tags:
  - mlx
base_model: google/gemma-3-270m

mlx-community/gemma-3-270m-5bit

This model mlx-community/gemma-3-270m-5bit was converted to MLX format from google/gemma-3-270m using mlx-lm version 0.26.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/gemma-3-270m-5bit")

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)