Image-Text-to-Text
MLX
Safetensors
mage_vl
vision-language-model
video-understanding
mage-vl
conversational
custom_code
8-bit precision
Instructions to use mlx-community/Mage-VL-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Mage-VL-8bit 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/Mage-VL-8bit") config = load_config("mlx-community/Mage-VL-8bit") # 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
File size: 465 Bytes
0aff9ba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"video_processor_type": "MageVLVideoProcessor",
"processor_class": "MageVLProcessor",
"auto_map": {
"AutoProcessor": "processing_mage_vl.MageVLProcessor",
"AutoVideoProcessor": "video_processing_mage_vl.MageVLVideoProcessor"
},
"max_frames": 768,
"fixed_num_frames": null,
"target_fps": null,
"min_pixels": 3136,
"max_pixels": 12845056,
"patch_size": 16,
"spatial_merge_size": 2,
"temporal_patch_size": 1,
"resize_frames": true
} |