---
language: en
license: mit
library_name: mlx
pipeline_tag: text-generation
tags:
- transformers
- mlx
base_model:
- MiniMaxAI/MiniMax-M2
---

# mlx-community/MiniMax-M2-mlx-8bit-gs32

This model [mlx-community/MiniMax-M2-mlx-8bit-gs32](https://huggingface.co/mlx-community/MiniMax-M2-mlx-8bit-gs32) was
converted to MLX format from [MiniMaxAI/MiniMax-M2](https://huggingface.co/MiniMaxAI/MiniMax-M2)
using mlx-lm version **0.28.1**.

## Recipe:
* 8-bit
* group-size 32
* 9 bits per weight (bpw)

You can find more similar MLX model quants for a single Apple Mac Studio M3 Ultra with 512 GB at https://huggingface.co/bibproj

---

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/MiniMax-M2-mlx-8bit-gs32")

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)
```