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Youssofal /

Qwen3.6-27B-Abliterated-Heretic-Uncensored-MLX-6bit

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Youssofal/Qwen3.6-27B-Abliterated-Heretic-Uncensored-MLX-6bit is an uncensored open-source model hosted on Hugging Face.

Text GenerationMLX LMsafetensorsLicense: apache-2.027Bmlxqwen3_5qwenqwen3.6densemultimodalvlmvisionvideoabliterateduncensoredhereticmpoaapple-silicon6-bitsomaconversational
README.md说明 / 使用方法

base_model: Youssofal/Qwen3.6-27B-Abliterated-Heretic-Uncensored-BF16 library_name: mlx pipeline_tag: text-generation license: apache-2.0 tags:

  • mlx
  • mlx-lm
  • qwen
  • qwen3.6
  • qwen3_5
  • dense
  • multimodal
  • vlm
  • vision
  • video
  • abliterated
  • uncensored
  • heretic
  • mpoa
  • apple-silicon
  • 6-bit
  • soma quantized_by: Youssofal

Qwen3.6-27B-Abliterated-Heretic-Uncensored-MLX-6bit

This is an MLX release of an abliterated, uncensored version of Qwen's Qwen3.6-27B with the source image/video payload retained, made from the published BF16 checkpoint.

By applying a Heretic-style MPOA pipeline with magnitude preservation on the Qwen3.6-27B dense text stack, the base refusal behavior was removed at the weight level. This MLX build keeps that text-side behavior in Apple Silicon format while retaining Qwen3.6-27B's vision/video payload in the repo.

Quick Benchmarks

CheckOriginal Qwen3.6-27BThis MLX Quant
Official 25-prompt refusal check20/25 refusals0/25 refusals
100-prompt refusal check92/100 refusals3/100 refusals

Methodology & Model Notes

Qwen3.6-27B is a 27.8B dense vision-language model with 64 text layers, hybrid linear/full attention (3 linear-attention + 1 full-attention per 4-layer group), and an integrated image + video vision tower.

This MLX variant was built directly from Youssofal/Qwen3.6-27B-Abliterated-Heretic-Uncensored-BF16 using dynamic layer-aware 6-bit affine MLX quantization with 64/32 group-size tiers. It is a dynamic, layer-aware quantization pass rather than a flat conversion. The retained multimodal payload includes the source vision/video tensors and processor files; direct image/video use depends on MLX runtime support for Qwen3.6 multimodal inputs.

Files

  • model-*.safetensors: quantized MLX text weights
  • model-vision-00001-of-00001.safetensors: retained BF16 vision/video tensor shard
  • model.safetensors.index.json: tensor-to-shard mapping, including retained vision tensors
  • config.json, generation_config.json, configuration.json: model config
  • tokenizer.json, tokenizer_config.json, chat_template.jinja: tokenizer + chat template
  • preprocessor_config.json, video_preprocessor_config.json: image + video processor configs
  • mlx_variant_metadata.json: build metadata

Running

from mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler

repo = "Youssofal/Qwen3.6-27B-Abliterated-Heretic-Uncensored-MLX-6bit"
model, tokenizer = load(repo)

messages = [{"role": "user", "content": "Write a short Python function that reverses a string."}]
prompt = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
    enable_thinking=False,
)

response = generate(
    model,
    tokenizer,
    prompt=prompt,
    max_tokens=256,
    sampler=make_sampler(temp=0.0),
)
print(response)

Model Architecture

SpecValue
Total Parameters27.8B (dense source)
Layers64
AttentionHybrid (3 linear-attention + 1 full-attention per 4-layer group)
Hidden Size5120
Familyqwen3_5
ModalityVision-language source; MLX text path locally validated
MLX Runtime ValidationText generation
Base ModelQwen/Qwen3.6-27B

Disclaimer

This model has had refusal behavior removed at the weight level. It will answer prompts that the base model would normally refuse. You are responsible for how you use it.

Credits

  • Base model: Qwen/Qwen3.6-27B
  • BF16 abliterated source: Youssofal/Qwen3.6-27B-Abliterated-Heretic-Uncensored-BF16
  • Refusal-removal pipeline: Heretic
  • MLX runtime and quantization: mlx-lm

License

This release inherits the base Qwen3.6-27B license.

Apache-2.0.

HUGGING FACE

上游数据

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来源与版本

作者
Youssofal
最近更新
2026/04/26
最新创建
2026/04/24
HF 趋势
未知
数据快照
2026/09/16
版本
未知
许可证
apache-2.0