Image-Text-to-Text
MLX
Safetensors
English
qwen2_5_vl
mlx-vlm
multimodal
document-understanding
unquantized
conversational
Instructions to use mlx-community/numind-NuExtract-2.0-8B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/numind-NuExtract-2.0-8B-MLX 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/numind-NuExtract-2.0-8B-MLX") config = load_config("mlx-community/numind-NuExtract-2.0-8B-MLX") # 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
- LM Studio
- Xet hash:
- fd0cd6059cd6ee1769ac558edef15b8809744ff20999f643b192783d3a4ea90e
- Size of remote file:
- 11.4 MB
- SHA256:
- 1a7aabe7a3b44651592a99607bb33066e6965260336be9218cccd53af161491d
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