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

osxest/Huihui-Qwen3.8-27B-abliterated-mlx-8Bit

osxest Qwen 27B 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/osxest%2FHuihui-Qwen3.8-27B-abliterated-mlx-8Bit"
Response includes
  • classification m1
  • files 14
  • hub_downloads_all_time 593
  • author_summary 9 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
593
184 last 30d - stable
Likes
0
Model age
7w ago
created 2026-08-19
Downloads over time
Now663→from230↑188%
208374540706230 on Aug 19663 on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

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
apache-2.0
Tags
transformers safetensors qwen3_5 image-text-to-text abliterated uncensored huihui qwen3 mlx mlx-my-repo conversational base_model:huihui-ai/Huihui-Qwen3.8-27B-abliterated

Related

Total size
26.6 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-19 07:21

Files by quantization

Auxiliary files 14 files 26.6 GB
model-00005-of-00006.safetensors 4.99 GB 9bb46102 download
model-00002-of-00006.safetensors 4.99 GB 624fcac1 download
model-00003-of-00006.safetensors 4.97 GB c12a9537 download
model-00001-of-00006.safetensors 4.94 GB da76c2e2 download
model-00004-of-00006.safetensors 4.93 GB 3a225274 download
model-00006-of-00006.safetensors 1.80 GB 3f0963ec download
tokenizer.json 19.1 MB 87a7830d download
model.safetensors.index.json 185 KB 0adfa998 download
chat_template.jinja 8.74 KB c0c686f9 download
config.json 3.99 KB e8c0add8 download
.gitattributes 1.53 KB 52373fe2 download
tokenizer_config.json 1.11 KB f57cfc38 download
README.md 1.05 KB 9257c86c download
generation_config.json 202 B 023756cf download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
pipeline_tag: image-text-to-text
base_model: huihui-ai/Huihui-Qwen3.8-27B-abliterated
tags:

  • abliterated
  • uncensored
  • huihui
  • qwen3
  • mlx
  • mlx-my-repo

osxest/Huihui-Qwen3.8-27B-abliterated-mlx-8Bit

The Model osxest/Huihui-Qwen3.8-27B-abliterated-mlx-8Bit was converted to MLX format from huihui-ai/Huihui-Qwen3.8-27B-abliterated using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("osxest/Huihui-Qwen3.8-27B-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. 2026-08-19Upload folder using huggingface_hub8446df41 KB
    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