How to use from
OpenClaw
Start the MLX server
# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "vanch007/Huihui-MiniCPM-V-4.6-abliterated-mlx-nvfp4"
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 "vanch007/Huihui-MiniCPM-V-4.6-abliterated-mlx-nvfp4" \
  --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"
Quick Links

Huihui-MiniCPM-V-4.6-abliterated-mlx-nvfp4

Converted from huihui-ai/Huihui-MiniCPM-V-4.6-abliterated with mlx-vlm from the current main branch.

Conversion

  • Source: huihui-ai/Huihui-MiniCPM-V-4.6-abliterated
  • Format: MLX
  • Quantization: bfloat16 + nvfp4
  • Processor files: processor_config.json + preprocessor_config.json

Smoke test

  • Prompt: Describe this image in one sentence.
  • Image: 64x64 solid red PNG
  • Result: The image is entirely filled with a solid red color.

Usage

python -m mlx_vlm.generate --model vanch007/Huihui-MiniCPM-V-4.6-abliterated-mlx-nvfp4 --max-tokens 32 --temperature 0.0 --trust-remote-code --prompt "Describe this image in one sentence." --image <path_to_image>
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