library_name: mlx-vlm pipeline_tag: image-text-to-text base_model: huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated base_model_relation: quantized tags:

• mlx
• mlx-vlm
• qwen3.6
• multimodal
• vision-language
• lm-studio
• abliterated

Huihui-Qwen3.6-35B-A3B-abliterated-mlx-4bit

MLX-VLM conversion of huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated.

Overview

• Format: MLX-VLM
• Precision: 4bit
• Size: 19G
• Source model type: Qwen3_5MoeForConditionalGeneration
• Source pipeline: image-text-to-text
• Intended runtime: mlx-vlm, LM Studio
• Quantization result: 4-bit affine

Validation

Local checks on Apple Silicon:

• model loading in mlx-vlm: passed
• text generation smoke test: passed
• image generation path smoke test: passed

Smoke-test logs were produced locally before upload.

Notes

This is an abliterated model conversion. Outputs may be less filtered than standard instruction-tuned models. Use responsibly and comply with applicable laws and platform policies.

Files

Important files in this repo:

• config.json
• generation_config.json
• chat_template.jinja
• tokenizer.json
• tokenizer_config.json
• model.safetensors.index.json
• model-*.safetensors

Usage

Text generation

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-4bit \
  --prompt "你好" \
  --max-tokens 128 \
  --trust-remote-code \
  --processor-kwargs '{"enable_thinking": false}'

Image prompt

mlx_vlm.generate \
  --model /path/to/Huihui-Qwen3.6-35B-A3B-abliterated-mlx-4bit \
  --image /path/to/example.png \
  --prompt "Describe this image." \
  --max-tokens 128 \
  --trust-remote-code \
  --processor-kwargs '{"enable_thinking": false}'