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VicTeamAgency/Qwen3.8-27B-Uncensored-GGUF

VicTeamAgency Qwen 27B GGUF
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  • classification m-uncensored
  • files 2
  • author_summary 1 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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Model age
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created 2026-10-16

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Qwen/Qwen3.8-27B this lineage
VicTeamAgency/Qwen3.8-27B-Uncensored-GGUF

Metadata

License
apache-2.0
Tags
gguf uncensored victeam base_model:Qwen/Qwen3.8-27B base_model:finetune:Qwen/Qwen3.8-27B license:apache-2.0 region:us

Related

Same base model
JonathanColetti/Qwen3.8-27B-Uncensored-GGUF 2.6M huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF 2.4M HauhauCS/Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-MTP-GGUF 2.3M 0bserverx/Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF 1.1M orcarouter/Qwen3.8-27B-Uncensored-FP8 140K
Total size
0 B
Files
2
Quantizations
1
Registered
2026-10-16 23:59
Last updated on HF
2026-10-16 23:54
Source huggingface.co/VicTeamAgency/Qwen3.8-27B-Uncensored-GGUF ↗ Base model Qwen/Qwen3.8-27B ↗

Files by quantization

Auxiliary files 2 files 2.46 KB
.gitattributes 1.48 KB a6344aac download
README.md 997 B 0a715e6e download

README current version from Hugging Face

license: apache-2.0
base_model: Qwen/Qwen3.8-27B
tags: [gguf, uncensored, victeam]

VicTeam Qwen 3.8 27B — Uncensored (GGUF)

Локальная расцензуренная модель от VicTeam Agency для агентной разработки на одной видеокарте.

Файл Квантизация Размер Когда брать
VicTeam-Qwen3.8-27B-Uncensored-Q4_K_XL.gguf Q4_K_XL ~17.4 ГБ основная: максимум качества
VicTeam-Qwen3.8-27B-Uncensored-IQ4_XS.gguf IQ4_XS ~14.4 ГБ целиком в 16 ГБ видеопамяти, быстрее

Запуск: llama.cpp (llama-server --jinja), через llama-swap.

Основа: Qwen3.8-27B (Alibaba Qwen, Apache 2.0); снятие отказов — abliteration
(сообщество huihui-ai, Apache 2.0); динамическая квантизация — Unsloth. Изменения: метаданные, имя.

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