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Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored
Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored is a abliterated and uncensored variant of Menlo/Lucy, published on Hugging Face by DavidAU. It is 4x1.7B total parameters (mixture-of-experts), single consumer GPU class and apache-2.0 licence. It is distributed across 4 repositories in Transformers, GGUF and GGUF (imatrix) formats, totalling 5.1K downloads.
Specification
- Model name
- Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored
- Source repository
- DavidAU/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored
- Base model
- Menlo/Lucy
- Publisher
- DavidAU
- Parameters
- 4x1.7B (mixture-of-experts)
- Hardware class
- 4B – 10B — single consumer GPU
- Licence
- apache-2.0
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- Transformers, GGUF, GGUF (imatrix)
- First indexed
- 27 Aug 2025
- Last updated
- 23 Dec 2025
Ablation technique
How Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-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
“This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats. The source code can also be used directly.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download mradermacher/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored-GGUF --local-dir ./qwen3-moe-4x1.7b-6.8b-lucys-song-uncensored
llama-cli -m ./qwen3-moe-4x1.7b-6.8b-lucys-song-uncensored/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "DavidAU/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve DavidAU/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored --trust-remote-codeDownloads and variants (3)
Every published repository of Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| mradermacher/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored-GGUF | GGUF | 4.8K |
| mradermacher/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored-i1-GGUF | GGUF (imatrix) | 169 |
| DavidAU/Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensoredsource | Transformers | 123 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Qwen3-MOE-4x1.7B-6.8B-Lucys-Song-Uncensored will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- Capability is inherited from Menlo/Lucy, not added by ablation — at 4x1.7B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- Declared licence is apache-2.0, but the terms that bind you are Menlo/Lucy’s — a re-release cannot grant more than its parent.
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-MOE-4x1.7B-6.8B-Lucys-Song-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 DavidAU, and does not independently verify publisher claims. See responsible use.