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otherwhere1/gemma-3-27b-it-abliterated-mlx-8Bit

otherwhere1 Gemma 27B multimodal second-order
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Response includes
  • classification m1
  • files 17
  • benchmarks 11 entries
  • hub_downloads_all_time 1,088
  • author_summary 2 models
  • readme_text full
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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
1K
39 last 30d - cooling
Likes
1
Model age
6mo ago
created 2026-03-24
Downloads over time
Now1.1K→from280↑290%
2395518631.2K280 on Mar 251.1K on Oct 111.1K on Oct 6MarAprMayJunJulAugSepOct
Mar 25 → Oct 11 · 68 snapshots · spans 200 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

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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 8-bit

Related

Total size
26.7 GB
Files
17
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-03-24 05:17

Files by quantization

Auxiliary files 17 files 26.8 GB
model-00001-of-00006.safetensors 4.96 GB feea7b0e download
model-00005-of-00006.safetensors 4.90 GB 14f28d38 download
model-00003-of-00006.safetensors 4.90 GB 8c967e05 download
model-00004-of-00006.safetensors 4.90 GB 858334aa download
model-00002-of-00006.safetensors 4.90 GB bbeddd23 download
model-00006-of-00006.safetensors 2.16 GB d327f970 download
tokenizer.json 31.8 MB 4667f208 download
tokenizer.model 4.47 MB 1299c11d download
tokenizer_config.json 1.10 MB ba114d51 download
model.safetensors.index.json 167 KB e15fa2c4 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.53 KB 5aece070 download
chat_template.jinja 1.50 KB 1117055a download
README.md 1000 B dc9f69f8 download
special_tokens_map.json 662 B 1a619324 download
generation_config.json 192 B f60a6730 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

otherwhere1/gemma-3-27b-it-abliterated-mlx-8Bit

The Model otherwhere1/gemma-3-27b-it-abliterated-mlx-8Bit was converted to MLX format from mlabonne/gemma-3-27b-it-abliterated using mlx-lm version 0.29.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("otherwhere1/gemma-3-27b-it-abliterated-mlx-8Bit")

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. 2026-03-24Upload README.md with huggingface_hub33d80e31000 B
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