Instructions to use alexmultiagent/MiniCPM5-1B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use alexmultiagent/MiniCPM5-1B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="alexmultiagent/MiniCPM5-1B-GGUF", filename="MiniCPM5-1B-Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use alexmultiagent/MiniCPM5-1B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "alexmultiagent/MiniCPM5-1B-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": "alexmultiagent/MiniCPM5-1B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
- Ollama
How to use alexmultiagent/MiniCPM5-1B-GGUF with Ollama:
ollama run hf.co/alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
- Unsloth Studio
How to use alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for alexmultiagent/MiniCPM5-1B-GGUF to start chatting
- Pi
How to use alexmultiagent/MiniCPM5-1B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf alexmultiagent/MiniCPM5-1B-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": "alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-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 alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use alexmultiagent/MiniCPM5-1B-GGUF with Docker Model Runner:
docker model run hf.co/alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
- Lemonade
How to use alexmultiagent/MiniCPM5-1B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull alexmultiagent/MiniCPM5-1B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MiniCPM5-1B-GGUF-Q4_K_M
List all available models
lemonade list
MiniCPM5-1B-GGUF (Q4_K_M)
Mirror of openbmb/MiniCPM5-1B-GGUF's
MiniCPM5-1B-Q4_K_M.gguf. Used by the IceSpiritAI_Chat Android app (MiniCPM5-1B
GGUF backend via llama.cpp; alternative to the default Qwen3.5-2B-MNN LLM).
Identity
| Field | Value |
|---|---|
| Source | huggingface.co/openbmb/MiniCPM5-1B-GGUF (official) |
| File | MiniCPM5-1B-Q4_K_M.gguf |
| Size | 688,065,920 bytes (656.30 MiB) |
| SHA-256 | 81b64d05a23b17b34c475f42b3e72fbde62d4b92cc34541f7a8031d0752deafa |
| Architecture | Standard LlamaForCausalLM (per OpenBMB model card) |
| Params | 1.08B (24 layers, GQA 16+2, ctx 131072) |
| Tokenizer | gpt2 (llama-bpe pre-tokenizer) |
| Uploaded | 2026-06-25 |
Why this mirror exists
IceSpiritAI_Chat is a dual-LLM Android app. The default LLM is
Qwen3.5-2B-MNN (small, fast, on-device MNN); the alternative is
MiniCPM5-1B-GGUF (slightly larger, higher-quality generations, served by a
llama.cpp native pipeline). Users in mainland China without reliable access to
huggingface.co can use this mirror or the ModelScope mirror
AlexZh/MiniCPM5-1B-GGUF.
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Base model
openbmb/MiniCPM5-1B