Instructions to use anikifoss/MiniMax-M2-HQ4_K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use anikifoss/MiniMax-M2-HQ4_K with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="anikifoss/MiniMax-M2-HQ4_K", filename="MiniMax-M2-HQ4_K-00001-of-00004.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use anikifoss/MiniMax-M2-HQ4_K with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf anikifoss/MiniMax-M2-HQ4_K # Run inference directly in the terminal: llama-cli -hf anikifoss/MiniMax-M2-HQ4_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf anikifoss/MiniMax-M2-HQ4_K # Run inference directly in the terminal: llama-cli -hf anikifoss/MiniMax-M2-HQ4_K
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 anikifoss/MiniMax-M2-HQ4_K # Run inference directly in the terminal: ./llama-cli -hf anikifoss/MiniMax-M2-HQ4_K
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 anikifoss/MiniMax-M2-HQ4_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf anikifoss/MiniMax-M2-HQ4_K
Use Docker
docker model run hf.co/anikifoss/MiniMax-M2-HQ4_K
- LM Studio
- Jan
- vLLM
How to use anikifoss/MiniMax-M2-HQ4_K with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "anikifoss/MiniMax-M2-HQ4_K" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "anikifoss/MiniMax-M2-HQ4_K", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/anikifoss/MiniMax-M2-HQ4_K
- Ollama
How to use anikifoss/MiniMax-M2-HQ4_K with Ollama:
ollama run hf.co/anikifoss/MiniMax-M2-HQ4_K
- Unsloth Studio new
How to use anikifoss/MiniMax-M2-HQ4_K 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 anikifoss/MiniMax-M2-HQ4_K 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 anikifoss/MiniMax-M2-HQ4_K to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for anikifoss/MiniMax-M2-HQ4_K to start chatting
- Pi new
How to use anikifoss/MiniMax-M2-HQ4_K with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf anikifoss/MiniMax-M2-HQ4_K
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": "anikifoss/MiniMax-M2-HQ4_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use anikifoss/MiniMax-M2-HQ4_K with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf anikifoss/MiniMax-M2-HQ4_K
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 anikifoss/MiniMax-M2-HQ4_K
Run Hermes
hermes
- Docker Model Runner
How to use anikifoss/MiniMax-M2-HQ4_K with Docker Model Runner:
docker model run hf.co/anikifoss/MiniMax-M2-HQ4_K
- Lemonade
How to use anikifoss/MiniMax-M2-HQ4_K with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull anikifoss/MiniMax-M2-HQ4_K
Run and chat with the model
lemonade run user.MiniMax-M2-HQ4_K-{{QUANT_TAG}}List all available models
lemonade list
Any Plan to Release MiniMax-M2.1 HQ4_K?
Dear @anikifoss , thank you for the excellent high-quality MiniMax-M2.0 HQ4_K quantized model! With the release of MiniMax-M2.1, could you kindly consider updating this quantized version for M2.1 as well? Iβd really appreciate it!
Ahh, Thank you so much for the update and for your quick work on this! Really appreciate you β this is super helpful. Happy holidays to you as well! ππ