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ngxson/LoRA-Qwen2.5-1.5B-Instruct-abliterated

ngxson Qwen 1.5B
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Response includes
  • classification m5
  • files 4
  • benchmarks 16 entries
  • author_summary 11 models
  • readme_text full
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What "m5" means · taxonomy
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Abliteration classifier · v1.0.0
M5
Primary method

Mergekit merge

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
M1 Direct removal →
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.
  • merge tag / mergekit / dare-ties in tags or name
  • no unusual architecture pattern (regular merge)
  • abliterated marker present
How we label → About M5 →
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
0
Likes
1
Descendants
1
in 1 direct fork
Model age
20mo ago
created 2025-01-23
Downloads over time
Now0→from0↑0%
00110 on Jan 22, 20250 on Oct 11Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 22, 2025 → Oct 11 · 129 snapshots · spans 627 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 1 direct fork

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
ngxson/LoRA-Qwen2.5-1.5B-Instruct-abliterated 1 fork
ggml-org/LoRA-Qwen2.5-1.5B-Instruct-abliterated-F16-GGUF↓ 130

Metadata

Tags
transformers safetensors mergekit peft base_model:Qwen/Qwen2.5-1.5B-Instruct base_model:finetune:Qwen/Qwen2.5-1.5B-Instruct endpoints_compatible region:us

Related

Other by ngxson
DeepSeek-R1-Distill-Qwen-7B-abliterated-GGUF 851 Llama-3-Instruct-abliteration-LoRA-8B-F16-GGUF 138 LoRA-Qwen2.5-7B-Instruct-abliterated-v3 0 LoRA-Qwen2.5-14B-Instruct-abliterated-v2 0 LoRA-phi-4-abliterated 0
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
179 MB
Files
4
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-01-23 22:16
Source huggingface.co/ngxson/LoRA-Qwen2.5-1.5B-Instruct-abliterated ↗ Base model Qwen/Qwen2.5-1.5B-Instruct ↗

Files by quantization

Auxiliary files 4 files 179 MB
adapter_model.safetensors 179 MB 329110bf download
.gitattributes 1.48 KB a6344aac download
README.md 782 B 784bdedf download
adapter_config.json 778 B ea283241 download

README current version from Hugging Face

base_model:

  • Qwen/Qwen2.5-1.5B-Instruct
  • huihui-ai/Qwen2.5-1.5B-Instruct-abliterated
    library_name: transformers
    tags:
  • mergekit
  • peft

Untitled LoRA Model (1)

This is a LoRA extracted from a language model. It was extracted using mergekit.

LoRA Details

This LoRA adapter was extracted from huihui-ai/Qwen2.5-1.5B-Instruct-abliterated and uses Qwen/Qwen2.5-1.5B-Instruct as a base.

Parameters

The following command was used to extract this LoRA adapter:

mergekit-extract-lora huihui-ai/Qwen2.5-1.5B-Instruct-abliterated Qwen/Qwen2.5-1.5B-Instruct OUTPUT_PATH --rank=64 --device=cuda

README history 1 version

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

  1. 2025-01-23Upload folder using huggingface_hub6c3ad5d782 B
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Discussions 1 thread

  1. 2025-04-28PRImprove language tagopen1 💬#1
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