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nguyenthilaitrieulong/GPTOSS-120B-Uncensored-HauhauCS-Aggressive

nguyenthilaitrieulong Gpt-oss 120B GGUF MoE 131K ctx
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Response includes
  • classification m8
  • files 3
  • benchmarks 16 entries
  • hub_downloads_all_time 470
  • author_summary 29 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
470
112 last 30d - stable
Likes
0
Model age
3mo ago
created 2026-06-21
Downloads over time
Now512→from44↑1,064%
2120037955944 on Jun 24512 on Oct 11512 on Oct 8JunJulAugSepOct
Jun 24 → Oct 11 · 55 snapshots · spans 109 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Arena-Battles 8335 LM-Arena
LM Arena Elo 1365.960115714145 LM-Arena
Arena-Elo-Lower 1359.0774821030143 LM-Arena
Arena-Elo-Upper 1372.842749325276 LM-Arena
Arena-Rank 28 LM-Arena
Entertainment 1.8 UGI
Hazardous 3.5 UGI
Natural Intelligence 33.68 UGI
Political lean -15.3% UGI
Sensitive-Info 19.48 UGI
SocPol 0.8 UGI
UGI 19.65 UGI
Willingness (10) 2 UGI
W10-Adherence 3 UGI
W10-Direct 1 UGI
Writing 38.52 UGI

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
apache-2.0
Languages
en
Tags
gguf uncensored abliterated mxfp4 moe gpt-oss en base_model:openai/gpt-oss-120b base_model:quantized:openai/gpt-oss-120b license:apache-2.0 endpoints_compatible region:us

Related

Total size
60.9 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-21 20:04

Files by quantization

Auxiliary files 3 files 60.9 GB
GPTOSS-120B-Uncensored-HauhauCS-Aggressive-MXFP4.gguf 60.9 GB 0ed271ff download
README.md 1.80 KB 6ec6819b download
.gitattributes 1.57 KB 0223bb23 download

README current version from Hugging Face


license: apache-2.0
base_model: openai/gpt-oss-120b
tags:

  • uncensored
  • abliterated
  • gguf
  • mxfp4
  • moe
  • gpt-oss
    language:
  • en

GPTOSS-120B-Uncensored-HauhauCS-Aggressive

Join the Discord for updates, roadmaps, projects, or just to chat.

Uncensored version of GPT-OSS 120B by OpenAI. This is the aggressive variant - tuned harder for fewer refusals.

No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.

Format

MXFP4 GGUF. This is the model's native precision - GPT-OSS was trained in MXFP4, so no further quantization is needed or recommended. Re-quantizing would only lose quality.

Works with llama.cpp, LM Studio, Ollama, and anything else that loads GGUFs.

Downloads

File Size
GPTOSS-120B-Uncensored-HauhauCS-Aggressive-MXFP4.gguf 61 GB

Specs

  • 117B total parameters, ~5.1B active per forward pass (MoE: 128 experts, top-4 routing)
  • 128K context
  • Based on openai/gpt-oss-120b

Recommended Settings

  • temperature: 1.0
  • top_k: 40
  • Everything else (top_p, min_p, repeat penalty, etc.) should be disabled - some clients enable these by default, turn them off

Required flag: --jinja to enable the Harmony response format (the model won't work correctly without it).

For llama.cpp:

llama-server -m model.gguf --jinja -fa -b 2048 -ub 2048

LM Studio

Compatible with Reasoning Effort custom buttons. To use them, put the model in:

LM Models\lmstudio-community\gpt-oss-120b-GGUF\

Hardware

Fits in ~61GB VRAM. Single H100 or equivalent. For lower VRAM, use --n-cpu-moe N in llama.cpp to offload MoE layers to CPU.

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-21Duplicate from HauhauCS/GPTOSS-120B-Uncensored-HauhauCS-Aggressive5df31d41.8 KB
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