Safetensors
MLX
mlx-vlm
qwen3_vl
qwen3-vl
vision-language
mobile-agent
apple-silicon
4-bit precision
Instructions to use clinan/GUI-Owl-1.5-2B-Instruct-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use clinan/GUI-Owl-1.5-2B-Instruct-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir GUI-Owl-1.5-2B-Instruct-MLX-4bit clinan/GUI-Owl-1.5-2B-Instruct-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
GUI-Owl-1.5-2B-Instruct-MLX-4bit
This repository contains an MLX-converted 4-bit version of mPLUG/GUI-Owl-1.5-2B-Instruct.
Source
- Original model:
mPLUG/GUI-Owl-1.5-2B-Instruct - Original architecture:
Qwen3VLForConditionalGeneration - Converted with:
mlx-vlm - Quantization:
4-bit affine
What Was Verified
This converted model was tested locally on Apple Silicon and successfully generated valid GUI action output from a Taobao shopping cart screenshot.
Example output:
Action: Click on the price section of the first item in the shopping cart.
<tool_call>
{"name": "mobile_use", "arguments": {"action": "click", "coordinate": [229, 566]}}
</tool_call>
Notes
- This is a converted derivative of the original model.
- Behavior may differ slightly from the original PyTorch checkpoint.
- The conversion was performed for local Apple Silicon inference and experimentation.
Minimal Usage
python -m mlx_vlm generate \
--model /path/to/GUI-Owl-1.5-2B-Instruct-MLX-4bit \
--image /path/to/screenshot.png \
--prompt 'Describe the next GUI action.'
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Model size
0.7B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit
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Model tree for clinan/GUI-Owl-1.5-2B-Instruct-MLX-4bit
Base model
mPLUG/GUI-Owl-1.5-2B-Instruct