Image-Text-to-Text
MLX
Safetensors
English
cohere_compass
mlx-vlm
vision-language
multimodal
cohere
north
quantized
conversational
4-bit precision
Instructions to use mlx-community/North-Micro-Vision-Instruct-nvfp4 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-nvfp4 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-nvfp4") config = load_config("mlx-community/North-Micro-Vision-Instruct-nvfp4") # 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
File size: 344 Bytes
4582323 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"size": {
"longest_edge": 25165824,
"shortest_edge": 4096
},
"patch_size": 16,
"temporal_patch_size": 2,
"merge_size": 2,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "CohereCompassProcessor",
"video_processor_type": "CohereCompassVideoProcessor"
}
|