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yimn-Aghosh/zegrate-uncensored

yimn-Aghosh Qwen
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     "https://abliteration.org/api/v1/models/yimn-Aghosh%2Fzegrate-uncensored"
Response includes
  • classification m-uncensored
  • files 12
  • benchmarks 16 entries
  • hub_downloads_all_time 116
  • 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
How we label → About M-U →
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
116
15 last 30d - stable
Likes
0
Model age
2mo ago
created 2026-07-14
Downloads over time
Now118→from94↑26%
9310211112094 on Jul 15118 on Oct 11118 on Oct 8JulAugSepOct
Jul 15 → Oct 11 · 53 snapshots · spans 88 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
BBH average 0.5662212997794785 OpenLLM-v2
IFEval instruct 0.8441247002398081 OpenLLM-v2
IFEval-Prompt 0.7874306839186691 OpenLLM-v2
MATH lvl 5 0 OpenLLM-v2
MMLU-Pro 0.4904421542553192 OpenLLM-v2
Entertainment 1.8 UGI
Hazardous 1.2 UGI
Natural Intelligence 18.5 UGI
Political lean -14.3% UGI
Sensitive-Info 17.56 UGI
SocPol 2.2 UGI
UGI 24.21 UGI
Willingness (10) 3.8 UGI
W10-Adherence 4.5 UGI
W10-Direct 3 UGI
Writing 29.79 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.

Qwen/Qwen2.5-14B-Instruct this lineage
yimn-Aghosh/zegrate-uncensored↓ 15

Metadata

Tags
peft safetensors base_model:adapter:Qwen/Qwen2.5-14B-Instruct lora transformers text-generation conversational arxiv:1910.09700 base_model:Qwen/Qwen2.5-14B-Instruct region:us

Related

Same base model
Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 252 rbinrs/Qwen2.5-14B-Instruct-abliterated-v2 204 sci4ai/Qwen2.5-14B-Instruct-Abliterated 155 zjj1993/unmuzzle-qwen14b-abliterated 70 Orion-zhen/Qwen2.5-14B-Instruct-Uncensored 56
Total size
97.2 MB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-07-14 14:53
Source huggingface.co/yimn-Aghosh/zegrate-uncensored ↗ Base model Qwen/Qwen2.5-14B-Instruct ↗

Files by quantization

Auxiliary files 12 files 112 MB
adapter_model.safetensors 97.2 MB 6847cf23 download
training_args.bin 5.64 KB d71536ef download
tokenizer.json 10.9 MB 145191e3 download
vocab.json 2.65 MB 4783fe10 download
merges.txt 1.59 MB 31349551 download
README.md 5.08 KB 41b99b38 download
tokenizer_config.json 4.58 KB eaed590d download
chat_template.jinja 2.45 KB bdf7919a download
.gitattributes 1.53 KB 52373fe2 download
adapter_config.json 858 B 31cea0b5 download
special_tokens_map.json 613 B ac23c0aa download
added_tokens.json 605 B 482ced46 download

README current version from Hugging Face

base_model: Qwen/Qwen2.5-14B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:

  • base_model:adapter:Qwen/Qwen2.5-14B-Instruct
  • lora
  • transformers

Model Card for Model ID

Model Details

Model Description

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Uses

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How to Get Started with the Model

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Training Details

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Evaluation

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Results

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Framework versions

  • PEFT 0.17.0

README history 1 version

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

  1. 2026-07-14Upload README.md with huggingface_hub45285485.1 KB
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