← back to catalog · registered 2026-08-22 13:56

tensorblock/mlabonne_gemma-3-12b-it-abliterated-v2-GGUF

tensorblock Gemma 12B GGUF multimodal second-order 131K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/tensorblock%2Fmlabonne_gemma-3-12b-it-abliterated-v2-GGUF"
Response includes
  • classification m8
  • files 4
  • benchmarks 11 entries
  • hub_downloads_all_time 1,793
  • author_summary 96 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
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=tensorblock (M8 quantization producer)
  • is_gguf=1
  • base_model='mlabonne/gemma-3-12b-it-abliterated-v2' looks abliterated -> assume M1
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.

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Downloads · lifetime
2K
109 last 30d - cooling
Likes
0
Model age
14mo ago
created 2025-07-28
Downloads over time
Now1.8K→from246↑640%
1677711.4K2K246 on Jul 30, 20251.8K on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 30, 2025 → Oct 11 · 102 snapshots · spans 438 days

Benchmarks

Benchmark Score Source
Entertainment 0.8 UGI
Hazardous 0.6 UGI
Natural Intelligence 8.16 UGI
Political lean -5.3% UGI
Sensitive-Info 8.74 UGI
SocPol 1.2 UGI
UGI 28.33 UGI
Willingness (10) 6.8 UGI
W10-Adherence 6.5 UGI
W10-Direct 7 UGI
Writing NA UGI

Genealogy 0 direct forks

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Metadata

License
gemma
Quantizations
Q2_K Q3_K
Tags
transformers gguf TensorBlock GGUF image-text-to-text base_model:mlabonne/gemma-3-12b-it-abliterated-v2 base_model:quantized:mlabonne/gemma-3-12b-it-abliterated-v2 license:gemma endpoints_compatible region:us conversational

Related

Total size
10.0 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2026-01-27 21:33

Files by quantization

Q3_K 1 file 5.60 GB
gemma-3-12b-it-abliterated-v2-Q3_K_M.gguf 5.60 GB 66279835 download
Q2_K 1 file 4.44 GB
gemma-3-12b-it-abliterated-v2-Q2_K.gguf 4.44 GB d50045e0 download
Auxiliary files 2 files 9.80 KB
README.md 7.42 KB da1a927d download
.gitattributes 2.39 KB 23aa55dc download

README current version from Hugging Face


license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
base_model: mlabonne/gemma-3-12b-it-abliterated-v2
tags:

  • TensorBlock
  • GGUF

TensorBlock

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mlabonne/gemma-3-12b-it-abliterated-v2 - GGUF

This repo contains GGUF format model files for mlabonne/gemma-3-12b-it-abliterated-v2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

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Prompt template

<bos><start_of_turn>user
{system_prompt}

{prompt}<end_of_turn>
<start_of_turn>model

Model file specification

Filename Quant type File Size Description
gemma-3-12b-it-abliterated-v2-Q2_K.gguf Q2_K 4.768 GB smallest, significant quality loss - not recommended for most purposes
gemma-3-12b-it-abliterated-v2-Q3_K_S.gguf Q3_K_S 5.458 GB very small, high quality loss
gemma-3-12b-it-abliterated-v2-Q3_K_M.gguf Q3_K_M 6.009 GB very small, high quality loss
gemma-3-12b-it-abliterated-v2-Q3_K_L.gguf Q3_K_L 6.480 GB small, substantial quality loss
gemma-3-12b-it-abliterated-v2-Q4_0.gguf Q4_0 6.887 GB legacy; small, very high quality loss - prefer using Q3_K_M
gemma-3-12b-it-abliterated-v2-Q4_K_S.gguf Q4_K_S 6.935 GB small, greater quality loss
gemma-3-12b-it-abliterated-v2-Q4_K_M.gguf Q4_K_M 7.301 GB medium, balanced quality - recommended
gemma-3-12b-it-abliterated-v2-Q5_0.gguf Q5_0 8.232 GB legacy; medium, balanced quality - prefer using Q4_K_M
gemma-3-12b-it-abliterated-v2-Q5_K_S.gguf Q5_K_S 8.232 GB large, low quality loss - recommended
gemma-3-12b-it-abliterated-v2-Q5_K_M.gguf Q5_K_M 8.445 GB large, very low quality loss - recommended
gemma-3-12b-it-abliterated-v2-Q6_K.gguf Q6_K 9.661 GB very large, extremely low quality loss
gemma-3-12b-it-abliterated-v2-Q8_0.gguf Q8_0 12.510 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/mlabonne_gemma-3-12b-it-abliterated-v2-GGUF --include "gemma-3-12b-it-abliterated-v2-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/mlabonne_gemma-3-12b-it-abliterated-v2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

README history 1 version

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

  1. 2025-07-28Upload folder using huggingface_hubcdf51027.4 KB
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