Instructions to use openbmb/MiniCPM-V-4.6-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM-V-4.6-gguf with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="openbmb/MiniCPM-V-4.6-gguf")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("openbmb/MiniCPM-V-4.6-gguf", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use openbmb/MiniCPM-V-4.6-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Use pre-built binary

# 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 openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Build from source code

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 openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Use Docker

docker model run hf.co/openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use openbmb/MiniCPM-V-4.6-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM-V-4.6-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM-V-4.6-gguf",
		"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"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

SGLang

How to use openbmb/MiniCPM-V-4.6-gguf with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "openbmb/MiniCPM-V-4.6-gguf" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM-V-4.6-gguf",
		"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"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "openbmb/MiniCPM-V-4.6-gguf" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM-V-4.6-gguf",
		"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"
						}
					}
				]
			}
		]
	}'

Ollama
How to use openbmb/MiniCPM-V-4.6-gguf with Ollama:
```
ollama run hf.co/openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
```

Unsloth Studio

How to use openbmb/MiniCPM-V-4.6-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for openbmb/MiniCPM-V-4.6-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for openbmb/MiniCPM-V-4.6-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for openbmb/MiniCPM-V-4.6-gguf to start chatting

How to use openbmb/MiniCPM-V-4.6-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "openbmb/MiniCPM-V-4.6-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use openbmb/MiniCPM-V-4.6-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

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 "openbmb/MiniCPM-V-4.6-gguf:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

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

Docker Model Runner
How to use openbmb/MiniCPM-V-4.6-gguf with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-V-4.6-gguf:Q4_K_M
```

Lemonade

How to use openbmb/MiniCPM-V-4.6-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM-V-4.6-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use openbmb/MiniCPM-V-4.6-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

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 openbmb/MiniCPM-V-4.6-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

not working with llama.cpp

by fawogin598 - opened 2 days ago

Discussion

fawogin598

2 days ago

•

edited 2 days ago

When I run this model and upload an image, the llama.cpp throws:
In the UI: Error: "This model supports: text files, PDFs"
through the local API: "image input is not supported - hint: if this is unexpected, you may need to provide the mmproj"

{
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "describe this image"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "data:image/png;base64,/9j/4AAQ...
          }
        }
      ]
    }
  ],
  "model": "MiniCPM-V-4_6-F16",
  "mmproj":"mmproj-model-f16"
}

logs:

[51243] 0.01.938.469 I srv          init: init: chat template, thinking = 1
[51243] 0.01.938.493 I srv          main: model loaded
[51243] 0.01.938.495 I srv          main: server is listening on http://127.0.0.1:51243
[51243] cmd_child_to_router:ready
[51243] cmd_child_to_router:info:{"id":"MiniCPM-V-4_6-Q4_K_M","aliases":["MiniCPM-V-4_6-Q4_K_M"],"tags":[],"object":"model","created":1786180099,"owned_by":"llamacpp","meta":{"vocab_type":2,"n_vocab":248094,"n_ctx":262144,"n_ctx_train":262144,"n_embd":1024,"n_params":752161600,"size":518145904}}
0.32.966.450 I srv  proxy_reques: proxying request to model MiniCPM-V-4_6-Q4_K_M on port 51243
[51243] 0.01.938.689 I srv  update_slots: all slots are idle
[51243] 0.01.938.694 I srv    operator(): child server monitoring thread started, waiting for EOF on stdin...
[51243] 0.01.939.675 W srv    operator(): got exception: {"error":{"code":500,"message":"image input is not supported - hint: if this is unexpected, you may need to provide the mmproj","type":"server_error"}}

Tested with Q4, then F16, with mmproj:

tc-mb

OpenBMB org 1 day ago

@fawogin598
This is a usage/configuration issue rather than a model support issue.
The "mmproj" field in the OpenAI request body is not supported and will not load the projector.
The projector must be specified when starting llama.cpp:

llama-server \
  -m MiniCPM-V-4_6-Q4_K_M.gguf \
  --mmproj mmproj-model-f16.gguf

You can refer to this document for guidance. It might be helpful.
https://github.com/OpenSQZ/MiniCPM-V-CookBook/blob/main/deployment/llama.cpp/minicpm-v4_6_llamacpp.md

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