Noct-Q-Uncensored-Qwen-Image-2.1
from Qwen/Qwen-Image-2.1
Qwen-Image-2.1-Uncensored is a abliterated and uncensored variant of Qwen/Qwen-Image-2.1, published on Hugging Face by 0xSojalSec. It is other licence. It is distributed across 56 repositories in OpenVINO and GGUF formats, totalling 95.6K downloads.
How Qwen-Image-2.1-Uncensored was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
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
“GGUF quantizations of Qwen/Qwen-Image-2.1 for local image generation using the original upstream base weights.”
Commands are templates — confirm the exact repository and quant file before use.
hf download 0xSojalSec/Qwen-Image-2.1-Uncensored-GGUF --local-dir ./qwen-image-2.1-uncensored
llama-cli -m ./qwen-image-2.1-uncensored/<file>.gguf -p "..."from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "0xSojalSec/Qwen-Image-2.1-Uncensored-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vllm serve 0xSojalSec/Qwen-Image-2.1-Uncensored-GGUF --trust-remote-codeEvery published repository of Qwen-Image-2.1-Uncensored, including quantised re-releases by other authors.
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 Qwen-Image-2.1-Uncensored is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with 0xSojalSec, and does not independently verify publisher claims. See responsible use.