Instructions to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD", filename="IQ4_XS/MiniMax-M2.7-abliterated-IQ4_XS-00001-of-00010.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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS # Run inference directly in the terminal: llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS # Run inference directly in the terminal: llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS # Run inference directly in the terminal: ./llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS # Run inference directly in the terminal: ./build/bin/llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
Use Docker
docker model run hf.co/GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
- LM Studio
- Jan
- vLLM
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
- Ollama
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with Ollama:
ollama run hf.co/GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
- Unsloth Studio
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD 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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD 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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD to start chatting
- Pi
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
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": "GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with Docker Model Runner:
docker model run hf.co/GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
- Lemonade
How to use GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS
Run and chat with the model
lemonade run user.MiniMax-M2.7-Abliterated-Heretic-GGUF-UD-IQ4_XS
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS# Run inference directly in the terminal:
llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XSUse 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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS# Run inference directly in the terminal:
./llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XSBuild 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 GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS# Run inference directly in the terminal:
./build/bin/llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XSUse Docker
docker model run hf.co/GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XSI'm using the Youssofal/MiniMax-M2.7-Abliterated-Heretic-GGUF model, but the q4 quantizations provided in the repository don't fit my system configuration (128GB RAM + 16GB VRAM), so I took the imatrix from unsloth (https://huggingface.co/unsloth/MiniMax-M2.7-GGUF/tree/main) and used their weights for quantization. Thanks a lot!
The advantage of unsloth's quantization is that it encodes different tensors with different precisions depending on their importance, so more important tensors are encoded with less loss. In the original (Youssofal) GGUF repository, all tensors are encoded with the same precision, which results in a significant loss of quality compared to unsloth's gguf.
So I tried to combine the best of both worlds.
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Model tree for GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD
Base model
MiniMaxAI/MiniMax-M2.7
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS# Run inference directly in the terminal: llama-cli -hf GreyManul/MiniMax-M2.7-Abliterated-Heretic-GGUF-UD:IQ4_XS