Instructions to use nativ-community/MiniCPM-V-4.7-1B-mxfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nativ-community/MiniCPM-V-4.7-1B-mxfp4 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("nativ-community/MiniCPM-V-4.7-1B-mxfp4")
config = load_config("nativ-community/MiniCPM-V-4.7-1B-mxfp4")

# 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

How to use nativ-community/MiniCPM-V-4.7-1B-mxfp4 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nativ-community/MiniCPM-V-4.7-1B-mxfp4"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "nativ-community/MiniCPM-V-4.7-1B-mxfp4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use nativ-community/MiniCPM-V-4.7-1B-mxfp4 with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nativ-community/MiniCPM-V-4.7-1B-mxfp4"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default nativ-community/MiniCPM-V-4.7-1B-mxfp4

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use nativ-community/MiniCPM-V-4.7-1B-mxfp4 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nativ-community/MiniCPM-V-4.7-1B-mxfp4"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "nativ-community/MiniCPM-V-4.7-1B-mxfp4" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

MiniCPM-V-4.7-1B-mxfp4 / conversion.json

prince-canuma

Add mxfp4 MLX conversion of openbmb/MiniCPM-V-4.7-1B (main e928101a)

92d3edb verified 4 days ago

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674 Bytes

	{
	"source_model": "openbmb/MiniCPM-V-4.7-1B",
	"source_revision": "984a89aafcd5160164f4f0d04b4be0f4eec03cb8",
	"mlx_vlm_revision": "e928101a144a3f11a27c7ef8d71b6d889b2d250c",
	"mlx_vlm_branch": "main",
	"mlx_vlm_version": "0.7.8",
	"dtype": "bfloat16",
	"format": "mxfp4",
	"conversion_options": {
	"quantize": true,
	"q_mode": "mxfp4",
	"q_bits": 4,
	"q_group_size": 32
	},
	"quantization": {
	"group_size": 32,
	"bits": 4,
	"mode": "mxfp4"
	},
	"weight_files": {
	"model.safetensors": {
	"size": 2656274552,
	"sha256": "7ad0d41ab92ff1eee0cb585dabb4b43c280cae21ff880f0108726c358d167cac"
	}
	},
	"license": "apache-2.0"
	}