---
license: apache-2.0
tags:
- bias-detection
- news-analysis
- media-bias
- journalism
- content-analysis
- mlx
language:
- en
pipeline_tag: text-generation
base_model: EmergentMethods/Qwen3-4B-BiasExpert
library_name: mlx
---

# Qwen3-4B-BiasExpert-dwq6-mlx

find and address bias in your code

This model [Qwen3-4B-BiasExpert-dwq6-mlx](https://huggingface.co/Qwen3-4B-BiasExpert-dwq6-mlx) was
converted to MLX format from [EmergentMethods/Qwen3-4B-BiasExpert](https://huggingface.co/EmergentMethods/Qwen3-4B-BiasExpert)
using mlx-lm version **0.26.0**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Qwen3-4B-BiasExpert-dwq6-mlx")

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)
```