Image-Text-to-Text
MLX
Safetensors
English
cohere_compass
mlx-vlm
vision-language
multimodal
cohere
north
quantized
conversational
6-bit
Instructions to use mlx-community/North-Micro-Vision-Instruct-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/North-Micro-Vision-Instruct-6bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/North-Micro-Vision-Instruct-6bit") config = load_config("mlx-community/North-Micro-Vision-Instruct-6bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- 08e1fde9cfd2d9484c3a5f342209e07dac20bd1845d9747edae7a823ea69282b
- Size of remote file:
- 2.66 GB
- SHA256:
- 564282d38108f0406bed6602fde32bc3f3877b3848f42cf0ad3d514aba9ced02
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