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TheCluster/Qwen3.5-9B-Ultra-Heretic-MLX-mxfp8

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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Model Card

<div align="center"><img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen3.5.png"></div>

Qwen3.5-9B Ultra Heretic

Quality: quantized (*mxfp8, group size: 32, 8.626 bpw*)

This is a abliterated (uncensored) version of Qwen/Qwen3.5-9B, made using Heretic v1.2.0 with Magnitude-Preserving Orthogonal Ablation (MPOA) and Self-Organizing Map Abliteration (SOMA)

Performance

MetricThis modelOriginal model ([Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B))
KL divergence0.10850 (by definition)
Refusals2/10086/100

Lower refusals indicate fewer content restrictions, while lower KL divergence indicates better preservation of the original model's capabilities.

Alternative fine-tuned version: TheCluster/Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT-HERETIC-UNCENSORED-MLX-mxfp8

Sampling Parameters:
  • —I 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
  • —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 `llmfan46/Qwen3.5-9B-ultra-heretic` using mlx-vlm version 0.4.