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}'