Instructions to use mlx-community/NuExtract3-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/NuExtract3-bf16 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/NuExtract3-bf16") config = load_config("mlx-community/NuExtract3-bf16") # 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
| { | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Qwen3VLImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_pixels": 16777216, | |
| "merge_size": 2, | |
| "min_pixels": 65536, | |
| "patch_size": 16, | |
| "rescale_factor": 0.00392156862745098, | |
| "temporal_patch_size": 2 | |
| }, | |
| "processor_class": "Qwen3VLProcessor", | |
| "video_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "fps": 2.0, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_frames": 768, | |
| "max_pixels": 786432, | |
| "merge_size": 2, | |
| "min_frames": 4, | |
| "min_pixels": 131072, | |
| "patch_size": 16, | |
| "rescale_factor": 0.00392156862745098, | |
| "temporal_patch_size": 2, | |
| "video_processor_type": "Qwen3VLVideoProcessor" | |
| } | |
| } | |