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library_name: mlx
license: apache-2.0
pipeline_tag: image-text-to-text
language:
- en
tags:
- mlx
- mlx-vlm
- vision-language
- multimodal
- cohere
- north
- quantized
base_model: CohereLabs/North-Micro-Vision-Instruct
base_model_relation: quantized
---
# North Micro Vision Instruct — 6-bit affine (MLX)
This repository contains an Apple MLX conversion of
[CohereLabs/North-Micro-Vision-Instruct](https://huggingface.co/CohereLabs/North-Micro-Vision-Instruct). 6-bit affine MLX quantization with group size 64.
It belongs to the
[North Vision MLX collection](https://huggingface.co/collections/mlx-community/north-vision-6a7c9be6ccc1cd992a83aecb), which includes BF16, affine
4/5/6/8-bit, MXFP4, MXFP8, and NVFP4 variants.
## Conversion details
- Source: [CohereLabs/North-Micro-Vision-Instruct](https://huggingface.co/CohereLabs/North-Micro-Vision-Instruct)
- Format: MLX / MLX-VLM
- Quantization: bits: 6; group size: 64; mode: affine
- MLX-VLM source revision: main at 7ee8eba3
The repository was regenerated and uploaded directly with the MLX-VLM
conversion CLI:
~~~bash
python -m mlx_vlm convert \
--hf-path CohereLabs/North-Micro-Vision-Instruct \
--mlx-path North-Micro-Vision-Instruct-6bit \
--quantize --q-bits 6 --q-group-size 64 --q-mode affine \
--upload-repo mlx-community/North-Micro-Vision-Instruct-6bit
~~~
## Usage
Cohere Compass support is available on the current MLX-VLM main branch.
Install it directly from GitHub:
~~~bash
pip install -U "mlx-vlm @ git+https://github.com/Blaizzy/mlx-vlm.git"
~~~
Run vision-language inference:
~~~bash
mlx_vlm.generate \
--model mlx-community/North-Micro-Vision-Instruct-6bit \
--image /path/to/image.jpg \
--prompt "Describe this image." \
--max-tokens 512 \
--temperature 0.0
~~~
You can also pass an image URL to --image.
## Notes
- MLX is optimized for Apple silicon.
- This repository changes the storage precision/quantization, not the source
model architecture or intended behavior.
- Refer to the
[original model card](https://huggingface.co/CohereLabs/North-Micro-Vision-Instruct) for capabilities,
limitations, licensing context, and responsible-use guidance.
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