kkxao/Qwen-Image-2.1-Text-Encoder-Heretic

AI model by kkxao

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The text encoder of Qwen/Qwen-Image-2.1 (a Qwen3-VL-8B-Instruct) with refusal behaviour removed via Heretic directional ablation. Drop-in replacement for the stock text encoder. Weights are bf16, same shapes, same parameter count — nothing else was changed. Measured by Heretic on mlabonne/harmfulbehaviors (test split) for refusals and mlabonne/harmlessalpaca for KL divergence — i.e. lower refusals and lower distribution shift on benign inputs. Refusal rate and general capability were re-checked with a separate script (different code, different refusal keyword set) rather than trusting the optimiser's own numbers: (e.g. "What is the capital of France?" → "The capital of France is Paris…") Heretic's documented defaults are ntrials = 200, nstartuptrials = 60. A first run with 100/20 was done for comparison: Doubling the search budget nearly halved the refusal rate and cut KL divergence by a third. 100 trials is not enough for this model. If you are abliterating something similar, use the documented…

kkxao/Qwen-Image-2.1-Text-Encoder-Heretic on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Qwen-Image-2.1 Text Encoder — Heretic (Abliterated)
  2. Results
  3. Independent verification
  4. ★ Search budget matters — measured, not assumed
  5. Pareto front
  6. Reproduction
  7. Gotchas worth knowing
  8. Usage
  9. Notes

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Model overview

kkxao/Qwen-Image-2.1-Text-Encoder-Heretic is a task-unspecified model repository published by kkxao on Hugging Face. A library was not reported.

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Task
Not reported
Library
Not reported
Recent downloads (30 days)
0
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0
Hugging Face trending score
0
Reported safetensors parameters
8,767,123,696
Architecture
Qwen3VLForConditionalGeneration
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-22T06:16:44.000Z
Last modified
2026-09-22T06:16:45.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: Qwen/Qwen3-VL-8B-Instruct

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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