Qwen3.8-27B-Uncensored
from Qwen/Qwen3.8-27B
Qwen3.8-27B-abliterated-oQ4e is a refusal-ablated open-weight language model, published on Hugging Face by root4k. It is 27B parameters and 48GB VRAM class class. It is distributed across 3 repositories in MLX format, totalling 6.3K downloads.
How Qwen3.8-27B-abliterated-oQ4e was modified, and what that implies.
Abliteration (directional ablation)
The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“This model was quantized using oQ (oMLX v0.6.3rc2) mixed-precision quantization.”
Commands are templates — confirm the exact repository and quant file before use.
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "root4k/Huihui-Qwen3.8-27B-abliterated-oQ4e-mtp"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vllm serve root4k/Huihui-Qwen3.8-27B-abliterated-oQ4e-mtp --trust-remote-codeEvery published repository of Qwen3.8-27B-abliterated-oQ4e, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| root4k/Huihui-Qwen3.8-27B-abliterated-oQ4e-mtpsource | MLX | 4.9K |
| root4k/Huihui-Qwen3.8-27B-abliterated-oQ4e-fp16-mtp | MLX | 1.4K |
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for Qwen3.8-27B-abliterated-oQ4e is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with root4k, and does not independently verify publisher claims. See responsible use.