Instructions to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/MiniMax-M2.1-REAP-50-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/MiniMax-M2.1-REAP-50-GGUF", filename="MiniMax-M2.1-REAP-50.IQ4_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with Ollama:
ollama run hf.co/mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
- Unsloth Studio
How to use mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/MiniMax-M2.1-REAP-50-GGUF to start chatting
- Pi
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mradermacher/MiniMax-M2.1-REAP-50-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": "mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-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 mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/MiniMax-M2.1-REAP-50-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/MiniMax-M2.1-REAP-50-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MiniMax-M2.1-REAP-50-GGUF-Q4_K_M
List all available models
lemonade list
REAP has been redone/fixed
FYI, an update: https://huggingface.co/datasets/0xSero/minimax-m2.1-reap-observations
REAP-20 Deprecated
REAP-30 Fixed
REAP-40 Fixed
REAP-50 Deprecated
Would be interesting to have the new GGUFs.
Can you please link what exact model you want us to quantize? https://huggingface.co/0xSero/MiniMax-M2.1-REAP-50-REPAIR-IN-PROGRESS no longer exists so we can't requantize it.
I assume you want us to quantize https://huggingface.co/0xSero/MiniMax-M2.1-REAP-30 and https://huggingface.co/0xSero/MiniMax-M2.1-REAP-40
We already did static quants for booth of them: https://huggingface.co/mradermacher/MiniMax-M2.1-REAP-30-GGUF and https://huggingface.co/mradermacher/MiniMax-M2.1-REAP-40-GGUF
Their weighted/imatrix quants are currently waiting for me to manually provide BF16 GGUFs as the F32 one is too large to run on 512 GiB of RAM. Please follow its status under hf.tst.eu/status.html
Many thanks!