Instructions to use baa-ai/MiniMax-M2.7-RAM-100GB-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use baa-ai/MiniMax-M2.7-RAM-100GB-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("baa-ai/MiniMax-M2.7-RAM-100GB-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use baa-ai/MiniMax-M2.7-RAM-100GB-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "baa-ai/MiniMax-M2.7-RAM-100GB-MLX"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "baa-ai/MiniMax-M2.7-RAM-100GB-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use baa-ai/MiniMax-M2.7-RAM-100GB-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "baa-ai/MiniMax-M2.7-RAM-100GB-MLX"
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 baa-ai/MiniMax-M2.7-RAM-100GB-MLX
Run Hermes
hermes
- MLX LM
How to use baa-ai/MiniMax-M2.7-RAM-100GB-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "baa-ai/MiniMax-M2.7-RAM-100GB-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "baa-ai/MiniMax-M2.7-RAM-100GB-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "baa-ai/MiniMax-M2.7-RAM-100GB-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }'
tyvm !
hi again , thanks for this !
i just checked that the 90GB is removed ? any reason
We have made it private for now, we were getting feedback that it was not giving great responses, so we thought we would test it a bit more before we make it available again.
We should have a final decision on its performance by this time tomorrow.
90G I tested very well
Are you able to use the 100GB version?
The way our algorithm works is the more memory budget you give it the better the results, I can't explain why, as that is part of our secret sauce, but even 10GB extra makes a lot of difference in performance.
If you let me know that exact max size you need, we might be able to get a version for that exact memory budget.
okok。 Let me try the 100G's.
When I use the 100G one, I often can't finish the task, but the 90G one suits me perfectly.
A minimalist line-art SVG animation sequence of a pelican riding a bicycle, side view. The pelican has a large beak with a slightly sagging throat pouch, wearing retro cycling cap and tiny round glasses. The bicycle is an old-fashioned penny-farthing with a large front wheel. The animation consists of 4 keyframes showing pedal motion: frame1 - left leg up, frame2 - right leg down, frame3 - left leg down, frame4 - right leg up. Smooth looping cycle. Clean black outlines on transparent background, flat vector style. Suitable for Lottie or SVG sprite animation. Use <g> tags and CSS @keyframes for wheel rotation and leg movement. The wheels rotate continuously. The pelican's beak bobs slightly up and down with each pedal stroke. Delightful whimsical motion.
my mac m4 max 128