Instructions to use openbmb/MiniCPM-o-4_5-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-o-4_5-gguf with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-o-4_5-gguf", dtype="auto") - llama-cpp-python
How to use openbmb/MiniCPM-o-4_5-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="openbmb/MiniCPM-o-4_5-gguf", filename="MiniCPM-o-4_5-F16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use openbmb/MiniCPM-o-4_5-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf openbmb/MiniCPM-o-4_5-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf openbmb/MiniCPM-o-4_5-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf openbmb/MiniCPM-o-4_5-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-4_5-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf openbmb/MiniCPM-o-4_5-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-4_5-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
Use Docker
docker model run hf.co/openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use openbmb/MiniCPM-o-4_5-gguf with Ollama:
ollama run hf.co/openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
- Unsloth Studio new
How to use openbmb/MiniCPM-o-4_5-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-4_5-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-4_5-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-4_5-gguf to start chatting
- Pi new
How to use openbmb/MiniCPM-o-4_5-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf openbmb/MiniCPM-o-4_5-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-4_5-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use openbmb/MiniCPM-o-4_5-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf openbmb/MiniCPM-o-4_5-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-4_5-gguf:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use openbmb/MiniCPM-o-4_5-gguf with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
- Lemonade
How to use openbmb/MiniCPM-o-4_5-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull openbmb/MiniCPM-o-4_5-gguf:Q4_K_M
Run and chat with the model
lemonade run user.MiniCPM-o-4_5-gguf-Q4_K_M
List all available models
lemonade list
how to use with llama.cpp when mmproj-model-f16.gguf is missing
I cannot find any source for mmproj-model-f16.gguf which is needed for running with llama.cpp
https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf/blob/main/vision/MiniCPM-o-4_5-vision-F16.gguf
This is the original mproj, which is used to provide the vison part of gguf. Because the omni model has so many modules, I want to use the unified name as much as possible. It will be very confusing to continue to use the name mproj.
is there any UI interface that you provide for inference and to use the capabilities of the model ? since LM studio doesnt even recognize the vision capabilities
Yes, we will provide a full set of demo code and a packaged docker that can be easily deployed by users, which is being processed. We hope to allow community users to truly use it on their own mac with the same effect as the online demo.
使用上llama-server运行时,使用提供的https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf/blob/main/vision/MiniCPM-o-4_5-vision-F16.gguf,加载了mmproj后,会报错GGML_ASSERT(false && "unsupported minicpmv version") failed。使用ollama下载运行,也会报这样的错误 Error: 500 Internal Server Error: llama runner process has terminated: GGML_ASSERT(false && "unsupported minicpmv version") failed
@lan0004
MiniCPM-o 4.5图文能力的更新已经合入llama.cp,您可以pull最新的代码来使用。
ollama可以用我们提供的分支https://github.com/tc-mb/ollama/tree/Suppport-MiniCPM-o-4.5,来编译执行后使用。
感谢回复,我试试
运行成功了,非常感谢。
how to use it with llama.cpp ? vision Futers ? what files download and run ? please