Instructions to use turnercore/minicpm5-1b-automaticity-v8 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 turnercore/minicpm5-1b-automaticity-v8 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 turnercore/minicpm5-1b-automaticity-v8:Q4_K_M # Run inference directly in the terminal: llama cli -hf turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf turnercore/minicpm5-1b-automaticity-v8:Q4_K_M # Run inference directly in the terminal: llama cli -hf turnercore/minicpm5-1b-automaticity-v8: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 turnercore/minicpm5-1b-automaticity-v8:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf turnercore/minicpm5-1b-automaticity-v8: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 turnercore/minicpm5-1b-automaticity-v8:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
Use Docker
docker model run hf.co/turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use turnercore/minicpm5-1b-automaticity-v8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "turnercore/minicpm5-1b-automaticity-v8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "turnercore/minicpm5-1b-automaticity-v8", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
- Ollama
How to use turnercore/minicpm5-1b-automaticity-v8 with Ollama:
ollama run hf.co/turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
- Unsloth Studio
How to use turnercore/minicpm5-1b-automaticity-v8 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 turnercore/minicpm5-1b-automaticity-v8 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 turnercore/minicpm5-1b-automaticity-v8 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for turnercore/minicpm5-1b-automaticity-v8 to start chatting
- Pi
How to use turnercore/minicpm5-1b-automaticity-v8 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf turnercore/minicpm5-1b-automaticity-v8: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": "turnercore/minicpm5-1b-automaticity-v8:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use turnercore/minicpm5-1b-automaticity-v8 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf turnercore/minicpm5-1b-automaticity-v8: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 turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use turnercore/minicpm5-1b-automaticity-v8 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf turnercore/minicpm5-1b-automaticity-v8: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 "turnercore/minicpm5-1b-automaticity-v8: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 turnercore/minicpm5-1b-automaticity-v8 with Docker Model Runner:
docker model run hf.co/turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
- Lemonade
How to use turnercore/minicpm5-1b-automaticity-v8 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull turnercore/minicpm5-1b-automaticity-v8:Q4_K_M
Run and chat with the model
lemonade run user.minicpm5-1b-automaticity-v8-Q4_K_M
List all available models
lemonade list
minicpm5-1b-automaticity-v8
Archival public release of Automaticity V8 LoRA, merged model, and GGUF exports research artifacts.
Training datasets, row-level prompts, predictions, and detailed evaluation evidence remain private. This release is retained for reproducibility and further testing; it is not a production promotion.
Contents
GGUF/MiniCPM5-1B.Q4_K_M.ggufGGUF/MiniCPM5-1B.Q8_0.gguflora_adapter/adapter_model.safetensorsmerged_model/model-00000-of-00001.safetensors
SHA-256
0fcb56885a3bcc67671b602ac9349882ab205a3eb2ba22baa97ba5eb162e4ba0 GGUF/MiniCPM5-1B.Q4_K_M.gguf771983e4d242dd82b276d1d459c83c13bc3346010139eb90294bb7313754bbcc GGUF/MiniCPM5-1B.Q8_0.gguf17bd35fc5b71384dc8f9b0f59f9dc995a9dc51f63cd1224c5e29a38db2ed1416 lora_adapter/adapter_model.safetensorscdefe06d91165d7adbe680638d6b301feed12ec715cf8eb1e0b355408adc7b0a merged_model/model-00000-of-00001.safetensors
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