๐๏ธ Vision & Multimodal
Collection
Multimodal models that understand images. On-device image description, visual question answering, and scene understanding โ all running on a phone. โข 1 item โข Updated
How to use dispatchAI/MiniCPM-V-4.6-mobile with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf dispatchAI/MiniCPM-V-4.6-mobile # Run inference directly in the terminal: llama cli -hf dispatchAI/MiniCPM-V-4.6-mobile
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf dispatchAI/MiniCPM-V-4.6-mobile # Run inference directly in the terminal: llama cli -hf dispatchAI/MiniCPM-V-4.6-mobile
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf dispatchAI/MiniCPM-V-4.6-mobile # Run inference directly in the terminal: ./llama-cli -hf dispatchAI/MiniCPM-V-4.6-mobile
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf dispatchAI/MiniCPM-V-4.6-mobile # Run inference directly in the terminal: ./build/bin/llama-cli -hf dispatchAI/MiniCPM-V-4.6-mobile
docker model run hf.co/dispatchAI/MiniCPM-V-4.6-mobile
How to use dispatchAI/MiniCPM-V-4.6-mobile with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dispatchAI/MiniCPM-V-4.6-mobile"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "dispatchAI/MiniCPM-V-4.6-mobile",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Describe this image in one sentence."
},
{
"type": "image_url",
"image_url": {
"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
}
}
]
}
]
}'docker model run hf.co/dispatchAI/MiniCPM-V-4.6-mobile
How to use dispatchAI/MiniCPM-V-4.6-mobile with Ollama:
ollama run hf.co/dispatchAI/MiniCPM-V-4.6-mobile
How to use dispatchAI/MiniCPM-V-4.6-mobile with Pi:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf dispatchAI/MiniCPM-V-4.6-mobile
# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
"providers": {
"llama-cpp": {
"baseUrl": "http://localhost:8080/v1",
"api": "openai-completions",
"apiKey": "none",
"models": [
{
"id": "dispatchAI/MiniCPM-V-4.6-mobile"
}
]
}
}
}# Start Pi in your project directory: pi
How to use dispatchAI/MiniCPM-V-4.6-mobile with Docker Model Runner:
docker model run hf.co/dispatchAI/MiniCPM-V-4.6-mobile
How to use dispatchAI/MiniCPM-V-4.6-mobile with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dispatchAI/MiniCPM-V-4.6-mobile
lemonade run user.MiniCPM-V-4.6-mobile-{{QUANT_TAG}}lemonade list
How to use dispatchAI/MiniCPM-V-4.6-mobile with Hermes Agent:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf dispatchAI/MiniCPM-V-4.6-mobile
# 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 dispatchAI/MiniCPM-V-4.6-mobile
hermes
How to use dispatchAI/MiniCPM-V-4.6-mobile with OpenClaw:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf dispatchAI/MiniCPM-V-4.6-mobile
# 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 "dispatchAI/MiniCPM-V-4.6-mobile" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
openclaw agent --local --agent main --message "Hello from Hugging Face"
OpenBMB's MiniCPM-V 2.6, a vision-language model that can SEE and THINK. Compressed for mobile deployment.
| Property | Value |
|---|---|
| Base | openbmb/MiniCPM-V-2_6 |
| Parameters | ~2.8 billion |
| Size | ~1.4 GB (GGUF) |
| Format | GGUF (llama.cpp) |
| License | Apache 2.0 |
Run multimodal AI (vision + language) on a phone. Image understanding, VQA, visual chatbots - all on-device.
huggingface-cli download dispatchAI/MiniCPM-V-4.6-mobile --local-dir ./models
./build/bin/main -m ./models/model.gguf -p "Describe this image" --image photo.jpg
We're not able to determine the quantization variants.