license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE language:

• en
• zh
• ru
• es
• fr
• it
• ja
• ko
• af
• de
• ar
• tr
• is
• pl
• sw
• sv
• nl
• he
• id
• uk
• fa
• pa
• pt
• ms
• fi
• el base_model:
• huihui-ai/Huihui-Qwen3.6-27B-abliterated library_name: mlx tags:
• abliterated
• uncensored
• decensored
• 9bit
• mixed-precision pipeline_tag: image-text-to-text

Qwen3.6-27B Abliterated (by huihui.ai)

This is another uncensored version of Qwen/Qwen3.6-27B, made by huihui.ai.

Quality: quantized (mixed quants per tensor, group size: 32, 9.450 bpw)

Most tensors use 8-bit affine quantization with a group size 32; some important tensors are saved in bf16.

Alternative version (from other source): TheCluster/Qwen3.6-27B-Heretic-MLX-mixed-9.4bit

Recommended settings

1. Sampling Parameters:
   • The developers suggest using the following sets of sampling parameters depending on the mode and task type:
     • Thinking mode for general tasks:
       temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
     • Thinking mode for precise coding tasks (e.g., WebDev):
       temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
     • Instruct (or non-thinking) mode for general tasks:
       temperature=0.7, top_p=0.8, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
     • Instruct (or non-thinking) mode for reasoning tasks:
       temperature=1.0, top_p=1.0, top_k=40, min_p=0.0, presence_penalty=2.0, repetition_penalty=1.0
   • For supported frameworks, you can adjust the presence_penalty parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.

Source

This model was converted to MLX format from huihui-ai/Huihui-Qwen3.6-27B-abliterated using mlx-vlm version 0.4.4.