metadata

license: gemma
library_name: mlx
pipeline_tag: text-generation
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
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  Google’s usage license. To do this, please ensure you’re logged in to Hugging
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base_model: google/gemma-3-1b-it
tags:
  - mlx

wolfofbackstreet/gemma-3-1b-it-4bit-mlx

This model wolfofbackstreet/gemma-3-1b-it-4bit-mlx was converted to MLX format from google/gemma-3-1b-it using mlx-lm version 0.22.5.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("wolfofbackstreet/gemma-3-1b-it-4bit-mlx")

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)