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RichardErkhov/huihui-ai_-_Llama-3.2-3B-Instruct-abliterated-4bits

RichardErkhov Llama 2.8B
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  • files 8
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
30
5 last 30d - stable
Likes
0
Model age
23mo ago
created 2024-10-26
Downloads over time
Now33→from2↑1,550%
01427412 on Oct 23, 202433 on Oct 1137 on Sep 10, 2025Oct '24Feb '25Jun '25Oct '25FebJunOct
Oct 23, 2024 → Oct 11 · 142 snapshots · spans 718 days

Metadata

Tags
safetensors llama 4-bit bitsandbytes region:us

Related

Total size
2.21 GB
Files
8
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-10-26 11:12

Files by quantization

Auxiliary files 8 files 2.22 GB
model.safetensors 2.21 GB 866ac2ca download
tokenizer.json 8.66 MB 777c28bc download
tokenizer_config.json 53.4 KB 610743cb download
README.md 1.71 KB ecbaf2ab download
.gitattributes 1.48 KB a6344aac download
config.json 1.38 KB fdefd90d download
special_tokens_map.json 439 B 344c8261 download
generation_config.json 184 B 40dfa313 download

README current version from Hugging Face

Quantization made by Richard Erkhov.

Github

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Llama-3.2-3B-Instruct-abliterated - bnb 4bits

Original model description:

library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:

  • abliterated
  • uncensored

🦙 Llama-3.2-3B-Instruct-abliterated

This is an uncensored version of Llama 3.2 3B Instruct created with abliteration (see this article to know more about it).

Special thanks to @FailSpy for the original code and technique. Please follow him if you're interested in abliterated models.

Evaluations

The following data has been re-evaluated and calculated as the average for each test.

Benchmark Llama-3.2-3B-Instruct Llama-3.2-3B-Instruct-abliterated
IF_Eval 76.55 76.76
MMLU Pro 27.88 28.00
TruthfulQA 50.55 50.73
BBH 41.81 41.86
GPQA 28.39 28.41

The script used for evaluation can be found inside this repository under /eval.sh, or click here

README history 1 version

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

  1. 2024-10-26uploaded readme4b9398a1.7 KB
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