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---
library_name: mlx
pipeline_tag: text-generation
tags:
- transformers
- mlx
license: other
license_name: modified-mit
license_link: https://github.com/MiniMax-AI/MiniMax-M2.1/blob/main/LICENSE
base_model:
- MiniMaxAI/MiniMax-M2.1
---
# mlx-community/MiniMax-M2.1-8bit-gs32
This model [mlx-community/MiniMax-M2.1-8bit-gs32](https://huggingface.co/mlx-community/MiniMax-M2.1-8bit-gs32) was
converted to MLX format from [MiniMaxAI/MiniMax-M2.1](https://huggingface.co/MiniMaxAI/MiniMax-M2.1)
using mlx-lm version **0.29.1**.
## 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-M2.1-8bit-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)
``` |