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

vd1990/gemma-3-12b-it-abliterated-v2-mlx-6Bit

vd1990 Gemma 13B multimodal second-order
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/vd1990%2Fgemma-3-12b-it-abliterated-v2-mlx-6Bit"
Response includes
  • classification m1
  • files 11
  • benchmarks 11 entries
  • hub_downloads_all_time 606
  • author_summary 3 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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
606
20 last 30d - cooling
Likes
0
Model age
15mo ago
created 2025-06-26
Downloads over time
Now616→from177↑248%
155323492660177 on Jul 9, 2025616 on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 9, 2025 → Oct 11 · 105 snapshots · spans 459 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

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
gemma
Tags
transformers safetensors gemma3_text text-generation mlx image-text-to-text conversational base_model:mlabonne/gemma-3-12b-it-abliterated-v2 base_model:quantized:mlabonne/gemma-3-12b-it-abliterated-v2 license:gemma text-generation-inference endpoints_compatible

Related

Total size
9.67 GB
Files
11
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-06-26 21:00

Files by quantization

Auxiliary files 11 files 9.70 GB
model-00001-of-00002.safetensors 5.00 GB ebc04122 download
model-00002-of-00002.safetensors 4.67 GB c7489e04 download
tokenizer.json 31.8 MB 4667f208 download
tokenizer.model 4.47 MB 1299c11d download
tokenizer_config.json 1.10 MB 7bdd14f0 download
model.safetensors.index.json 110 KB 1ea780d2 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.13 KB d8402058 download
README.md 1001 B 43617cb5 download
special_tokens_map.json 662 B 1a619324 download
added_tokens.json 35.0 B e17bde03 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:

  • mlx

vd1990/gemma-3-12b-it-abliterated-v2-mlx-6Bit

The Model vd1990/gemma-3-12b-it-abliterated-v2-mlx-6Bit was converted to MLX format from mlabonne/gemma-3-12b-it-abliterated-v2 using mlx-lm version 0.22.3.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("vd1990/gemma-3-12b-it-abliterated-v2-mlx-6Bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

README history 1 version

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

  1. 2025-06-26Upload README.md with huggingface_hubec3a0a81001 B
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration