Qwen3-Next-80B-A3B-Instruct-abliterated
80BQwen
↓ 26.8K♥ 69 repos
Qwen2.5-72B-Instruct-abliterated
Qwen2.5-72B-Instruct-abliterated is a refusal-ablated variant of Qwen/Qwen2.5-72B-Instruct, published on Hugging Face by huihui-ai. It is 72B parameters, multi-GPU class and other licence. It is distributed across 17 repositories in Transformers, GGUF, AWQ and EXL2 formats, totalling 54.5K downloads.
Specification
- Model name
- Qwen2.5-72B-Instruct-abliterated
- Source repository
- huihui-ai/Qwen2.5-72B-Instruct-abliterated
- Base model
- Qwen/Qwen2.5-72B-Instruct
- Publisher
- huihui-ai
- Parameters
- 72B
- VRAM required
- ~44.5 GB at Q4_K_M, 4k context (estimated) — runs on 48 GB cards
- Hardware class
- 50B – 100B — multi-GPU
- Licence
- other
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- Transformers, GGUF, AWQ, EXL2, GGUF (imatrix), MLX, GPTQ
- First indexed
- 1 Oct 2024
- Last updated
- 25 Sept 2026
Ablation technique
How Qwen2.5-72B-Instruct-abliterated 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 is an uncensored version of Qwen/Qwen2.5-72B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
Ollama (publisher-documented)
ollama run huihui_ai/qwen2.5-abliterate:72bllama.cpp / GGUF
hf download zetasepic/Qwen2.5-72B-Instruct-abliterated-GGUF --local-dir ./qwen2.5-72b-instruct-abliterated
llama-cli -m ./qwen2.5-72b-instruct-abliterated/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "huihui-ai/Qwen2.5-72B-Instruct-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve huihui-ai/Qwen2.5-72B-Instruct-abliterated --trust-remote-codeDownloads and variants (16)
Every published repository of Qwen2.5-72B-Instruct-abliterated, including quantised re-releases by other authors.
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Qwen2.5-72B-Instruct-abliterated 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 Qwen/Qwen2.5-72B-Instruct, not added by ablation — at 72B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- Declared licence is other, but the terms that bind you are Qwen/Qwen2.5-72B-Instruct’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 Qwen2.5-72B-Instruct-abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with huihui-ai, and does not independently verify publisher claims. See responsible use.