---
pipeline_tag: text-generation
license: other
license_name: modified-mit
license_link: https://github.com/MiniMax-AI/MiniMax-M2.5/blob/main/LICENSE
library_name: mlx
base_model: MiniMaxAI/MiniMax-M2.5
tags:
- mlx
---

# catalystsec/MiniMax-M2.5-4bit-DWQ

This model was quantized to 4-bit using DWQ with mlx-lm version **0.30.7**.

| Parameter                 | Value                          |
|---------------------------|--------------------------------|
| DWQ learning rate         | 3e-7                           |
| Batch size                | 1                              |
| Dataset                   | `allenai/tulu-3-sft-mixture`   |
| Initial validation loss   | 0.077                          |
| Final validation loss     | 0.053                          |
| Relative KL reduction     | ≈31 %                          |
| Tokens processed          | ≈1.11 M                        |

## Perplexity

Evaluated on 210 samples of 512 tokens from the default mlx-lm calibration data.

| Model | Perplexity |
|-------|-----------|
| 3-bit | 7.802 |
| 3-bit DWQ | 7.434 |
| 4-bit | 6.581 |
| 4-bit DWQ | **6.431** |

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("catalystsec/MiniMax-M2.5-4bit-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)
```