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

KYUNGYONG/gemma-3-27b-it-abliterated-mlx-3Bit

KYUNGYONG Gemma 28B 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/KYUNGYONG%2Fgemma-3-27b-it-abliterated-mlx-3Bit"
Response includes
  • classification m1
  • files 12
  • benchmarks 11 entries
  • hub_downloads_all_time 975
  • author_summary 13 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
975
24 last 30d - cooling
Likes
0
Model age
18mo ago
created 2025-03-21
Downloads over time
Now981→from12↑8,075%
03597191.1K12 on Mar 19, 2025981 on Oct 11981 on Oct 10Mar '25Jun '25Sep '25Dec '25MarJunSep
Mar 19, 2025 → Oct 11 · 121 snapshots · spans 571 days

Benchmarks

Benchmark Score Source
Entertainment 1.5 UGI
Hazardous 2.4 UGI
Natural Intelligence 29.6 UGI
Political lean -7.7% UGI
Sensitive-Info 20.32 UGI
SocPol 2.4 UGI
UGI 41.05 UGI
Willingness (10) 8.2 UGI
W10-Adherence 7.5 UGI
W10-Direct 9 UGI
Writing 35.62 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 image-text-to-text mlx conversational base_model:mlabonne/gemma-3-27b-it-abliterated base_model:quantized:mlabonne/gemma-3-27b-it-abliterated license:gemma text-generation-inference endpoints_compatible 3-bit

Related

Total size
11.6 GB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-03-21 04:16

Files by quantization

Auxiliary files 12 files 11.6 GB
model-00001-of-00003.safetensors 4.98 GB 458a4151 download
model-00002-of-00003.safetensors 4.97 GB 96deaa3a download
model-00003-of-00003.safetensors 1.63 GB 3f213a50 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 167 KB 65eea94f download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.48 KB 7b1de86c download
README.md 992 B a3db583c 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-3-27b-it-abliterated
tags:

  • mlx

KYUNGYONG/gemma-3-27b-it-abliterated-mlx-3Bit

The Model KYUNGYONG/gemma-3-27b-it-abliterated-mlx-3Bit was converted to MLX format from mlabonne/gemma-3-27b-it-abliterated using mlx-lm version 0.22.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("KYUNGYONG/gemma-3-27b-it-abliterated-mlx-3Bit")

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. 2025-03-21Upload README.md with huggingface_hub1e204d2992 B
    Loading...

Discussions 1 thread

  1. 2025-03-25<pad> repeat problemopen1 💬#1
    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