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Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF

Devarui379 Llama 1B GGUF 131K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/Devarui379%2FLlama-3.2-1B-Instruct-abliterated-Q8_0-GGUF"
Response includes
  • classification m8
  • files 3
  • benchmarks 21 entries
  • hub_downloads_all_time 507
  • author_summary 3 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
507
116 last 30d - stable
Likes
0
Model age
2.0y ago
created 2024-10-03
Downloads over time
Now576→from14↑4,014%
021142263314 on Oct 2, 2024576 on Oct 12Oct '24Feb '25Jun '25Oct '25FebJunOct
Oct 2, 2024 → Oct 12 · 146 snapshots · spans 740 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 8523 LM-Arena
LM Arena Elo 1067.4348646816593 LM-Arena
Arena-Elo-Lower 1060.145342091014 LM-Arena
Arena-Elo-Upper 1074.7243872723045 LM-Arena
Arena-Rank 207 LM-Arena
BBH average 0.3342846024127643 OpenLLM-v2
IFEval instruct 0.6294964028776978 OpenLLM-v2
IFEval-Prompt 0.5101663585951941 OpenLLM-v2
MATH lvl 5 0.02945619335347432 OpenLLM-v2
MMLU-Pro 0.16821808510638298 OpenLLM-v2
Entertainment 0.2 UGI
Hazardous 0 UGI
Natural Intelligence 6.89 UGI
Political lean -6.0% UGI
Sensitive-Info 2.34 UGI
SocPol 0.5 UGI
UGI 6.56 UGI
Willingness (10) 1.5 UGI
W10-Adherence 1 UGI
W10-Direct 2 UGI
Writing 11.82 UGI

Genealogy 0 direct forks

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Metadata

License
llama3.2
Languages
en
Tags
transformers gguf abliterated uncensored llama-cpp gguf-my-repo llama text-generation-inference en base_model:meta-llama/Llama-3.2-1B-Instruct base_model:quantized:meta-llama/Llama-3.2-1B-Instruct license:llama3.2

Related

Total size
1.49 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-10-03 14:37

Files by quantization

Auxiliary files 3 files 1.49 GB
llama-3.2-1b-instruct-abliterated-q8_0.gguf 1.49 GB e3074a9e download
README.md 1.96 KB 06ab301c download
.gitattributes 1.56 KB c044fa6c download

README current version from Hugging Face


base_model:

  • meta-llama/Llama-3.2-1B-Instruct
    library_name: transformers
    license: llama3.2
    tags:
  • abliterated
  • uncensored
  • llama-cpp
  • gguf-my-repo
  • llama
  • text-generation-inference
    language:
  • en

Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF

This model was converted to GGUF format
Refer to the original model card for more details on the model.

You can use it with LM Studio or other mentioned methods below.

image/png

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Devarui379/Llama-3.2-1B-Instruct-abliterated-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated-q8_0.gguf -c 2048

README history 4 versions

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

  1. 2024-10-03Update README.md09a23972 KB
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  2. 2024-10-03Update README.mdc98704a1.8 KB
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  3. 2024-10-03Update README.md6d29b941.7 KB
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  4. 2024-10-03Upload README.md with huggingface_hub74143292 KB
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