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---
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 |
## MMLU-PRO Benchmark
| Model | Score |
|-------|:-----:|
| 3-bit DWQ | **66.1** |
| 3-bit | 62.0 |
<img src="minimax_3e-7_mmlu.png" width="600" alt="MMLU-Pro Benchmark">
## 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)
``` |