DeepSeek-R1-Distill-Qwen-14B-uncensored
14BQwenuncensored
from deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
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DeepSeek-R1-Distill-Qwen-14B-abliterated-v2
DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 is a refusal-ablated variant of deepseek-ai/DeepSeek-R1-Distill-Qwen-14B, published on Hugging Face by huihui-ai. It is 14B parameters and 24GB VRAM class class. It is distributed across 28 repositories in Transformers, GGUF, GPTQ and GGUF (imatrix) formats, totalling 22.4K downloads.
Specification
- Model name
- DeepSeek-R1-Distill-Qwen-14B-abliterated-v2
- Source repository
- huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2
- Base model
- deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
- Publisher
- huihui-ai
- Parameters
- 14B
- VRAM required
- ~9.3 GB at Q4_K_M, 4k context (estimated) — runs on 12 GB cards
- Hardware class
- 10B – 25B — 24GB VRAM class
- Licence
- Not declared
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- Transformers, GGUF, GPTQ, GGUF (imatrix), MLX
- First indexed
- 23 Jan 2025
- Last updated
- 4 Jun 2026
Ablation technique
How DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 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 deepseek-ai/DeepSeek-R1-Distill-Qwen-14B 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/deepseek-r1-abliterated:14bllama.cpp / GGUF
hf download mradermacher/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2-GGUF --local-dir ./deepseek-r1-distill-qwen-14b-abliterated-v2
llama-cli -m ./deepseek-r1-distill-qwen-14b-abliterated-v2/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 --trust-remote-codeDownloads and variants (27)
Every published repository of DeepSeek-R1-Distill-Qwen-14B-abliterated-v2, 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.
- DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 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 deepseek-ai/DeepSeek-R1-Distill-Qwen-14B, not added by ablation — at 14B 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.
- No licence is declared on this repository, which is a compliance problem in itself. Resolve it against the base model’s terms before use.
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 DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 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.