MiniCPM-V 4.6
Collection
MLX variants of MiniCPM-V 4.6, 1.3B parameters (SigLIP2 400M vision encoder + Qwen3.5-0.8B LLM), repo: https://huggingface.co/openbmb/MiniCPM-V-4.6 • 7 items • Updated • 1
mlx-community/MiniCPM-V-4.6-4bit
This model was converted to MLX format from openbmb/MiniCPM-V-4.6
using mlx-vlm version 0.4.5.
Refer to the original model card for more details on the model.
Use with mlx
pip install -U mlx-vlm
python -m mlx_vlm.generate --model mlx-community/MiniCPM-V-4.6-4bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>
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Model size
1B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit
Model tree for mlx-community/MiniCPM-V-4.6-4bit
Base model
openbmb/MiniCPM-V-4.6
# 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/MiniCPM-V-4.6-4bit") config = load_config("mlx-community/MiniCPM-V-4.6-4bit") # 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)