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

# catalystsec/MiniMax-M2-3bit-DWQ

This model was quantized to 3-bit using DWQ with mlx-lm version **0.28.4**.

| Parameter                 | Value                          |
|---------------------------|--------------------------------|
| DWQ learning rate         | 3e-7                           |
| Batch size                | 1                              |
| Dataset                   | `allenai/tulu-3-sft-mixture`   |
| Initial validation loss   | 0.146                          |
| Final validation loss     | 0.088                          |
| Relative KL reduction     | ≈40 %                         |
| Tokens processed          | ≈1.09 M                        |

<img src="minimax_3e-7.png" width="600" alt="Training loss curve">

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("catalystsec/MiniMax-M2-3bit-DWQ")
prompt = "hello"

if tokenizer.chat_template is not None:
    prompt = tokenizer.apply_chat_template(
        [{"role": "user", "content": prompt}],
        add_generation_prompt=True,
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
print(response)
```