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---
library_name: transformers
license: gemma
license_link: https://ai.google.dev/gemma/terms
pipeline_tag: text-generation
extra_gated_heading: Access CodeGemma on Hugging Face
extra_gated_prompt: To access CodeGemma 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
widget:
- text: '<start_of_turn>user Write a Python function to calculate the nth fibonacci
number.<end_of_turn> <start_of_turn>model
'
inference:
parameters:
max_new_tokens: 200
tags:
- mlx
base_model: google/codegemma-1.1-7b-it
---
# mlx-community/codegemma-1.1-7b-it-6bit
The Model [mlx-community/codegemma-1.1-7b-it-6bit](https://huggingface.co/mlx-community/codegemma-1.1-7b-it-6bit) was converted to MLX format from [google/codegemma-1.1-7b-it](https://huggingface.co/google/codegemma-1.1-7b-it) using mlx-lm version **0.24.1**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/codegemma-1.1-7b-it-6bit")
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)
```
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