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zebulon-prime/Qwen3.8-27B-Dominatrix-abliterated
Qwen3.8-27B-Dominatrix-abliterated is a image-text-to-text model from zebulon-prime. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
allura-org/Qwen3.8-27B-Dominatrix with the refusal direction from huihui-ai/Huihui-Qwen3.8-27B-abliterated projected out, recomputed against Dominatrix's own weights rather than transferred as an
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From the Hugging Face model README
allura-org/Qwen3.8-27B-Dominatrix with the refusal direction from huihui-ai/Huihui-Qwen3.8-27B-abliterated projected out, recomputed against Dominatrix's own weights rather than transferred as an additive delta.
The goal was to keep Dominatrix's roleplay prose intact while picking up huihui's uncensored behaviour. Perplexity on in-domain RP text is essentially unchanged, and the large majority of tensors are untouched.
An NVFP4 quant, built for SGLang with DFlash 2 speculative decoding, is at Qwen3.8-27B-Dominatrix-abliterated-MTP-NVFP4.
This is a VL architecture (Qwen3_5ForConditionalGeneration). Load it with
AutoModelForImageTextToText:
from transformers import AutoModelForImageTextToText, AutoTokenizer
import torch
model = AutoModelForImageTextToText.from_pretrained(
"zebulon-prime/Qwen3.8-27B-Dominatrix-abliterated",
dtype=torch.bfloat16, device_map="cuda:0", trust_remote_code=True)
tok = AutoTokenizer.from_pretrained("zebulon-prime/Qwen3.8-27B-Dominatrix-abliterated")
Do not use AutoModelForCausalLM. For model_type: qwen3_5 it silently resolves to the
text-only Qwen3_5ForCausalLM, which drops the vision and MTP tensors on load. A PEFT adapter
applied afterwards will match no modules, making merge_and_unload() a silent no-op that
still writes a complete-looking checkpoint.
preserve_thinking off, reasoning_effort medium rather than xhigh).Only the residual-stream output projections in the upper layers were modified.
Upstream's sampler guidance carries over: temperature 1.0–1.25 with either min_p 0.1 or
top_p 0.95; some users prefer 0.7 temperature and nothing else.
Reasoning is supported and preserved. Disable per request with
chat_template_kwargs={"enable_thinking": false}. With thinking enabled, a low max_tokens
can return empty content because the entire budget went to the reasoning block.
Fidelity was checked against stock Dominatrix on in-domain roleplay text. No standardised refusal-rate or safety evaluation was run; uncensored behaviour was confirmed only by spot-checking generations.