Instructions to use openbmb/MiniCPM-o-2_6-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use openbmb/MiniCPM-o-2_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-o-2_6-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf openbmb/MiniCPM-o-2_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-o-2_6-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf openbmb/MiniCPM-o-2_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-o-2_6-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf openbmb/MiniCPM-o-2_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-o-2_6-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
Use Docker
docker model run hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use openbmb/MiniCPM-o-2_6-gguf with Ollama:
ollama run hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
- Unsloth Studio
How to use openbmb/MiniCPM-o-2_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-o-2_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-o-2_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-o-2_6-gguf to start chatting
- Pi
How to use openbmb/MiniCPM-o-2_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-o-2_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-o-2_6-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use openbmb/MiniCPM-o-2_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-o-2_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-o-2_6-gguf:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use openbmb/MiniCPM-o-2_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-o-2_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-o-2_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-o-2_6-gguf with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
- Lemonade
How to use openbmb/MiniCPM-o-2_6-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
Run and chat with the model
lemonade run user.MiniCPM-o-2_6-gguf-Q4_K_M
List all available models
lemonade list
Error: llama runner process has terminated: exit status 2 when running ollama
I run this command:
ollama run hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M
and has this error:
Error: llama runner process has terminated: exit status 2
Specs:
- CUDA: v12
- GPU T4 Tesla
- Running in SageMaker instance (AWS)
- Python 3.11.11
Model has been downloaded but failed to run. I tried ollama list and confirmed that model has been downloaded:
hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M 577cda2e3886 5.7 GB 21 seconds ago
I also tried running on llama-cpp-python but it also has a lot of errors.
Please help. I am desperate.
Thank you very much.
I get an error message as well running this on Ollama. I'm not desperate though, I hope this can be solved in the coming weeks. π
same problem
Hello, it is based on llama.cpp and can use gguf to inference, then my changes have not been merged into the official yet, and you may need to wait until the merge.
I run this command:
ollama run hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_Mand has this error:
Error: llama runner process has terminated: exit status 2Specs:
- CUDA: v12
- GPU T4 Tesla
- Running in SageMaker instance (AWS)
- Python 3.11.11
Model has been downloaded but failed to run. I tried ollama list and confirmed that model has been downloaded:
hf.co/openbmb/MiniCPM-o-2_6-gguf:Q4_K_M 577cda2e3886 5.7 GB 21 seconds agoI also tried running on llama-cpp-python but it also has a lot of errors.
Please help. I am desperate.
Thank you very much.
same for me
Same here
ollama run hf.co/openbmb/MiniCPM-o-2_6-gguf:latest
python --version
Python 3.12.7
system_profiler SPDisplaysDataType
Graphics/Displays:
Apple M4 Max:
Chipset Model: Apple M4 Max
Type: GPU
Bus: Built-In
Total Number of Cores: 40
Vendor: Apple (0x106b)
Metal Support: Metal 3
Same thing here! I downloaded MiniCPM-o-2_6 from the official Ollama site and it seems to work correctly in Windows CLI. However this is a Q4 model and its complete name (as listed by Ollama) is: ZimaBlueAI/MiniCpm-o-2_6:latest. Unfortunately there are no other quantization models in the "ZimaBlueAI" directory, q4 is the only one and it comes with out the projector-model from the original hf directory (hf.co/openbmb/MiniCPM-o-2_6-gguf). This is the place where I downloaded the Q6 and the Q8, but with the same result. It seems the 'exit-status 2' failure has something to do with the projector-model, witch came with both, Q6 and Q8, but not with the ZimaBlue-Q4 version. I have tried to run the Q6 model by manipulating its 'manifest-file' in the local ollama directory of my system, by excluding the projector-model. Voila! This time it started without error message. However the model wasn't capable to answer any question, instead started to go wild and run in loops etc...
still facing the same error , did anyone figured it out please make a post on r/LocalLLaMA i
Our model may not yet support direct deployment with Ollama, we will push forward as soon as possible
Thank you for keeping us updated!!
same error I got, What should be the solution?
https://ollama.com/openbmb/minicpm-o2.6
You can directly use our adapted ollama model. Run ollama with one line of code.
ollama run openbmb/minicpm-o2.6
