metadata

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 was converted to MLX format from EmergentMethods/Qwen3-4B-BiasExpert using mlx-lm version 0.26.0.

Use with mlx

pip install mlx-lm

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)