README.md

---
base_model: princeton-nlp/gemma-2-9b-it-SimPO
tags:
- alignment-handbook
- generated_from_trainer
- mlx
datasets:
- princeton-nlp/gemma2-ultrafeedback-armorm
license: mit
pipeline_tag: text-generation
library_name: mlx
model-index:
- name: princeton-nlp/gemma-2-9b-it-SimPO
  results: []
---

# mlx-community/gemma-2-9b-it-SimPO-8bit

This model [mlx-community/gemma-2-9b-it-SimPO-8bit](https://huggingface.co/mlx-community/gemma-2-9b-it-SimPO-8bit) was
converted to MLX format from [princeton-nlp/gemma-2-9b-it-SimPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO)
using mlx-lm version **0.26.0**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/gemma-2-9b-it-SimPO-8bit")

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)
```