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fwizzer1/Qwen2.5-2B-Uncensored-Reasoning-RU

fwizzer1 Qwen 2B
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Response includes
  • classification m-uncensored
  • files 12
  • benchmarks 16 entries
  • author_summary 2 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 · 30-day
9
↑ 14% in 90 days
Likes
0
Model age
7w ago
created 2026-08-17
Downloads over time
Now8→from7↑14%
77887 on Aug 198 on Aug 318 on Aug 26Aug
Aug 19 → Aug 31 · 7 snapshots · spans 12 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 0.39278765079776884 OpenLLM-v2
IFEval instruct 0.4940047961630696 OpenLLM-v2
IFEval-Prompt 0.4011090573012939 OpenLLM-v2
MATH lvl 5 0.01283987915407855 OpenLLM-v2
MMLU-Pro 0.27992021276595747 OpenLLM-v2
Entertainment 0.9 UGI
Hazardous 1.8 UGI
Natural Intelligence 8.66 UGI
Political lean -12.1% UGI
Sensitive-Info 9.9 UGI
SocPol 0.5 UGI
UGI 14.93 UGI
Willingness (10) 2.5 UGI
W10-Adherence 2 UGI
W10-Direct 3 UGI
Writing 22.17 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/Qwen2.5-1.5B-Instruct this lineage
fwizzer1/Qwen2.5-2B-Uncensored-Reasoning-RU↓ 9

Metadata

Tags
peft safetensors base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct lora sft transformers trl text-generation conversational arxiv:1910.09700 base_model:Qwen/Qwen2.5-1.5B-Instruct region:us

Related

Other by fwizzer1
Qwen3.5-2B-Uncensored-Reasoning-RU 20
Same base model
arzaan789/qwen2.5-1.5b-uncensored 1K DeKodez/Qwen2.5-1.5B-Instruct-abliterated 429 ElementMerc/qwen2.5-1.5b-abliterated 257 sbussiso/Qwen2.5-1.5B-abliterated 244 ops-malware/qwen2.5-1.5b-abliterated 238
Total size
71.5 MB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-17 18:17
Source huggingface.co/fwizzer1/Qwen2.5-2B-Uncensored-Reasoning-RU ↗ Base model Qwen/Qwen2.5-1.5B-Instruct ↗

Files by quantization

Auxiliary files 12 files 82.4 MB
optimizer.pt 36.2 MB 52f5ab49 download
adapter_model.safetensors 35.3 MB d4a452ea download
rng_state.pth 13.9 KB 333dfbb9 download
training_args.bin 5.24 KB b310ba6d download
scheduler.pt 1.04 KB e0eca67b download
tokenizer.json 10.9 MB 3fd16973 download
README.md 5.10 KB 8ca9ee33 download
chat_template.jinja 2.50 KB 9840d40f download
trainer_state.json 2.24 KB 4e21f3db download
.gitattributes 1.53 KB 52373fe2 download
adapter_config.json 1.18 KB 9a03decb download
tokenizer_config.json 724 B df142d09 download

README current version from Hugging Face

base_model: Qwen/Qwen2.5-1.5B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:

  • base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct
  • lora
  • sft
  • transformers
  • trl

Model Card for Model ID

Model Details

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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 0.20.0
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