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---
license: gemma
tags:
- gemma3
- gemma
- google
- functiongemma
- mlx
pipeline_tag: text-generation
library_name: mlx
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: 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.
extra_gated_button_content: Acknowledge license
base_model: google/functiongemma-270m-it
---
# mlx-community/functiongemma-270m-it-4bit
This model [mlx-community/functiongemma-270m-it-4bit](https://huggingface.co/mlx-community/functiongemma-270m-it-4bit) was
converted to MLX format from [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it)
using mlx-lm version **0.28.4**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/functiongemma-270m-it-4bit")
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)
```
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