Instructions to use beshkenadze/moondream3-preview-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use beshkenadze/moondream3-preview-mlx-4bit 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("beshkenadze/moondream3-preview-mlx-4bit") config = load_config("beshkenadze/moondream3-preview-mlx-4bit") # 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: 537 Bytes
a49db27 | 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 | {
"architectures": [
"HfMoondream"
],
"auto_map": {
"AutoConfig": "hf_moondream.HfConfig",
"AutoModelForCausalLM": "hf_moondream.HfMoondream"
},
"config": {
"skills": [
"query",
"caption",
"detect",
"point"
]
},
"model_type": "moondream3",
"quantization": {
"group_size": 64,
"bits": 4,
"mode": "affine"
},
"quantization_config": {
"group_size": 64,
"bits": 4,
"mode": "affine"
},
"torch_dtype": "bfloat16",
"transformers_version": "4.51.1"
}
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