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

nabi-chan/Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MLX-6bit

nabi-chan Qwen 35B MoE 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/nabi-chan%2FQwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MLX-6bit"
Response includes
  • classification m1
  • files 14
  • hub_downloads_all_time 920
  • author_summary 12 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
920
29 last 30d - cooling
Likes
0
Model age
5mo ago
created 2026-04-27

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now928→from215↑332%
179453726999215 on Apr 29928 on Oct 11AprMayJunJulAugSepOct
Apr 29 → Oct 11 · 63 snapshots · spans 165 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
Languages
en ko zh ja
Tags
mlx safetensors qwen3_5_moe mlx-6bit quantized apple-silicon Qwen Qwen3.6 Qwen3_5_moe reasoning distillation chain-of-thought

Related

Total size
27.4 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-04-27 10:51

Files by quantization

Auxiliary files 14 files 27.4 GB
model-00001-of-00006.safetensors 4.96 GB bda27a46 download
model-00005-of-00006.safetensors 4.90 GB 508fd83f download
model-00003-of-00006.safetensors 4.90 GB 820451ea download
model-00002-of-00006.safetensors 4.90 GB 002948c2 download
model-00004-of-00006.safetensors 4.87 GB 64497f63 download
model-00006-of-00006.safetensors 2.82 GB c3171d03 download
tokenizer.json 19.1 MB 87a7830d download
model.safetensors.index.json 203 KB fcbaf151 download
config.json 64.7 KB 8ce71989 download
tokenizer_config.json 9.28 KB 92774a9b download
chat_template.jinja 7.87 KB f7a7d1b0 download
README.md 4.53 KB 2155b065 download
.gitattributes 1.53 KB 52373fe2 download
processor_config.json 1.27 KB 7ad6acdf download

README current version from Hugging Face


library_name: mlx
license: "apache-2.0"
pipeline_tag: text-generation
language:

  • en
  • ko
  • zh
  • ja
    tags:
  • mlx
  • "mlx-6bit"
  • quantized
  • safetensors
  • apple-silicon
  • Qwen
  • Qwen3.6
  • Qwen3_5_moe
  • reasoning
  • distillation
  • chain-of-thought
  • mixture-of-experts
  • moe
  • lora
  • unsloth
  • abliterated
  • uncensored
    datasets:
  • lordx64/reasoning-distill-opus-4-7-max-sft
    base_model:
  • huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated
    model-index: []

🌌 huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated converted to MLX 6-bit

About This Quantization

Apple Sllicon / MLX 6-bit

Quickstart

Install

pip install -U "mlx-lm>=0.31.2"

Python

from mlx_lm import load, generate

model, tokenizer = load("nabi-chan/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MLX-6bit")
print(generate(model, tokenizer, prompt="Explain quantum entanglement simply.", max_tokens=128))

CLI

python3 -m mlx_lm generate \
  --model nabi-chan/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MLX-6bit \
  --prompt "Write a haiku about Apple Silicon." \
  --max-tokens 128

Quantization Details

Property Value
Method MLX affine quantization
Bits / weight 6
Group size 64
Non-quant dtype bfloat16
Quantizer version mlx : 0.31.2 / mlx-lm : 0.31.3 / mlx-vlm: 0.4.4

[!WARNING]
Protected tensors keep their original dtype. In VLM models, vision tensors and some guarded layers may remain unquantized.


Everything below is huihui-ai's original model card, preserved verbatim.


huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated

This is an uncensored version of lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled created with abliteration (see remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.

ollama

Please use the latest version of ollama

You can use huihui_ai/qwen3.6-abliterated:35b-Claude-4.7 directly,

ollama run huihui_ai/Qwen3.6-abliterated:35b-Claude-4.7

Usage Warnings

  • Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.

  • Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.

  • Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.

  • Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.

  • Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.

  • No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.

Donation

Your donation helps us continue our further development and improvement, a cup of coffee can do it.
  • bitcoin:
  bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
  • Support our work on Ko-fi!

README history 5 versions

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

  1. 2026-04-27Add files using upload-large-folder tool12602774.5 KB
    Loading...
  2. 2026-04-27Update README.md760753f4.7 KB
    Loading...
  3. 2026-04-27Update README.md9f84b444.7 KB
    Loading...
  4. 2026-04-27Update README.mdf79547b4.8 KB
    Loading...
  5. 2026-04-27Add files using upload-large-folder tool26de0b34.8 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