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lukaskremla/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-6Bit

lukaskremla Qwen 35B MoE multimodal second-order
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/lukaskremla%2FHuihui-Qwen3.6-35B-A3B-abliterated-mlx-6Bit"
Response includes
  • classification m1
  • files 14
  • author_summary 3 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 · 30-day
108
↑ 905% in 90 days
Likes
0
Model age
3mo ago
created 2026-06-17
Downloads over time
Now573→from57↑905%
3122942762557 on Jun 17573 on Aug 30573 on Aug 28JunJulAug
Jun 17 → Aug 30 · 14 snapshots · spans 74 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_moe image-text-to-text abliterated uncensored mlx mlx-my-repo conversational base_model:huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated base_model:quantized:huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated license:apache-2.0

Related

Total size
26.2 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-17 19:10

Files by quantization

Auxiliary files 14 files 26.3 GB
model-00003-of-00006.safetensors 4.89 GB f6e91405 download
model-00004-of-00006.safetensors 4.89 GB 297e8c62 download
model-00002-of-00006.safetensors 4.87 GB 6a0be3a6 download
model-00001-of-00006.safetensors 4.87 GB 85c11c0c download
model-00005-of-00006.safetensors 4.86 GB 810317e3 download
model-00006-of-00006.safetensors 1.86 GB 76d57f74 download
tokenizer.json 19.1 MB 87a7830d download
model.safetensors.index.json 183 KB d155a813 download
config.json 22.6 KB a5a7bd01 download
chat_template.jinja 7.58 KB a8755d82 download
.gitattributes 1.53 KB 52373fe2 download
README.md 1.15 KB 6d721e75 download
tokenizer_config.json 1.11 KB f57cfc38 download
generation_config.json 202 B 023756cf download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.6-35B-A3B/blob/main/LICENSE
pipeline_tag: image-text-to-text
base_model: huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated
tags:

  • abliterated
  • uncensored
  • mlx
  • mlx-my-repo

lukaskremla/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-6Bit

The Model lukaskremla/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-6Bit was converted to MLX format from huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("lukaskremla/Huihui-Qwen3.6-35B-A3B-abliterated-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)
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