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

vanch007/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated-mlx-bf16

vanch007 Qwen 35B MoE 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/vanch007%2FHuihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated-mlx-bf16"
Response includes
  • classification m1
  • files 26
  • hub_downloads_all_time 1,063
  • author_summary 27 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
1K
35 last 30d - cooling
Likes
1
Model age
6mo ago
created 2026-03-17
Downloads over time
Now1.1K→from140↑665%
934508071.2K140 on Mar 181.1K on Oct 111.1K on Oct 10MarAprMayJunJulAugSepOct
Mar 18 → Oct 11 · 69 snapshots · spans 207 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

Tags
mlx-vlm safetensors qwen3_5_moe mlx multimodal vision-language qwen lm-studio abliterated image-text-to-text conversational base_model:huihui-ai/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated

Related

Total size
65.4 GB
Files
26
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-03-18 01:44

Files by quantization

Auxiliary files 26 files 65.4 GB
model-00001-of-00014.safetensors 4.98 GB 17ec48df download
model-00013-of-00014.safetensors 4.71 GB 2bebc2c1 download
model-00005-of-00014.safetensors 4.71 GB e91ca68c download
model-00009-of-00014.safetensors 4.71 GB ae57029c download
model-00010-of-00014.safetensors 4.70 GB bbb00db5 download
model-00006-of-00014.safetensors 4.70 GB 7b7db641 download
model-00012-of-00014.safetensors 4.70 GB 713a408c download
model-00011-of-00014.safetensors 4.70 GB 897fabc2 download
model-00007-of-00014.safetensors 4.70 GB 5b62ef4a download
model-00004-of-00014.safetensors 4.70 GB dfbdb8a7 download
model-00002-of-00014.safetensors 4.70 GB bf50fb4b download
model-00008-of-00014.safetensors 4.70 GB 99184ebb download
model-00003-of-00014.safetensors 4.70 GB 66431e07 download
model-00014-of-00014.safetensors 4.01 GB f0c9f90e download
tokenizer.json 19.1 MB 87a7830d download
vocab.json 6.41 MB 0aa0ce06 download
model.safetensors.index.json 104 KB d6f9781b download
chat_template.jinja 7.56 KB c4c3ecbb download
config.json 3.31 KB 892c455e download
README.md 2.28 KB c19ccf72 download
.gitattributes 1.53 KB 52373fe2 download
processor_config.json 1.27 KB 7ad6acdf download
tokenizer_config.json 1.14 KB aeb7593d download
preprocessor_config.json 390 B 2ea84a43 download
video_preprocessor_config.json 385 B 3ba673a5 download
generation_config.json 244 B 5ff346d6 download

README current version from Hugging Face


library_name: mlx-vlm
pipeline_tag: image-text-to-text
base_model: huihui-ai/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated
base_model_relation: quantized
tags:

  • mlx
  • mlx-vlm
  • multimodal
  • vision-language
  • qwen
  • lm-studio
  • abliterated

Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated-mlx-bf16

MLX-VLM conversion of huihui-ai/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated.

Overview

  • Format: MLX-VLM
  • Precision: bf16
  • Size: about 66G
  • Source model is preserved as a vision-language model for mlx-vlm
  • Local validation passed for text generation and abliterated behavior regression

Conversion Notes

This conversion keeps the model in the mlx-vlm layout and includes the compatibility fixes required for reliable use with MLX-VLM and LM Studio:

  • restored a Qwen VL-compatible chat_template.jinja
  • aligned bos/eos/pad token ids in config.json
  • preserved image and video prompt token handling

Validation

Local checks performed on Apple Silicon:

  • text generation smoke test: passed
  • abliterated regression set: 6/6 non-refused
  • refusal_rate = 0.0
  • eval run id: 20260317_200129
  • median cleaned response length: 563 chars
  • eval settings: max_tokens=320, temperature=0.0, prefill_step_size=128

This is a behavior regression check, not a mathematical proof of equivalence.

Files

Important files in this repo:

  • config.json
  • chat_template.jinja
  • processor_config.json
  • tokenizer.json
  • model-00001-of-00014.safetensors ... model-00014-of-00014.safetensors
  • model.safetensors.index.json

Usage

mlx-vlm text generation

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated-mlx-bf16 \
  --prompt "你好" \
  --max-tokens 256 \
  --prefill-step-size 128

mlx-vlm image prompt

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.5-35B-A3B-Claude-4.6-Opus-abliterated-mlx-bf16 \
  --image /path/to/example.png \
  --prompt "请简短描述这张图片。" \
  --max-tokens 128 \
  --prefill-step-size 128

LM Studio

This repo is intended to work as an MLX model in LM Studio after download or sync. The included chat template already contains the required Qwen vision tokens.

README history 2 versions

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

  1. 2026-03-18Upload README.md with huggingface_hubd00dbf62.3 KB
    Loading...
  2. 2026-03-17Add files using upload-large-folder toolfb839fc1.2 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