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: 1,813 Bytes
0aff9ba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | {
"data_format": "channels_first",
"default_to_square": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_processor_type": "Qwen2VLImageProcessor",
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"max_pixels": 4000000,
"merge_size": 2,
"min_pixels": 3136,
"patch_size": 16,
"processor_class": "MageVLProcessor",
"auto_map": {
"AutoProcessor": "processing_mage_vl.MageVLProcessor",
"AutoVideoProcessor": "video_processing_mage_vl.MageVLVideoProcessor"
},
"codec": {
"engine": "hevc",
"target_canvas": 32,
"group_size": 32,
"images_per_group": 4,
"patch": 14,
"min_group_frames": 8,
"max_group_frames": 64,
"spatial_mask_mode": "off",
"dcvc": {
"qp": 42,
"reset_interval": 64,
"intra_period": -1,
"max_side": 0,
"seq_len_frames": 0,
"patch": 16,
"canvas_token_side": null,
"num_sampled_frames": 256,
"grouping_mode": "readiness",
"readiness_sum_threshold_mode": "auto",
"group_size": 32,
"images_per_group": 4,
"max_pixels": 150000,
"min_group_frames": 8,
"max_group_frames": 128,
"readiness_coverage_bins": 3,
"readiness_delta_ratio": 0.05,
"bitcost_grid": "sub",
"bitcost_pct": 99,
"decode_backsearch_max": 16,
"canvas_format": "jpg",
"per_frame_cap_ratio": 1.2,
"bottom_atten": 0.5,
"bottom_band": 0.1,
"threshold_scale": 1.0,
"random_select": false,
"random_seed": 0
}
},
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"longest_edge": 4000000,
"shortest_edge": 3136
},
"temporal_patch_size": 1
}
|