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ahoybrotherbear
/
MiniMax-M2.5-3bit-MLX

Text Generation
MLX
quantized
3bit
minimax_m2
conversational
apple-silicon
Model card Files Files and versions
xet
Community

Instructions to use ahoybrotherbear/MiniMax-M2.5-3bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use ahoybrotherbear/MiniMax-M2.5-3bit-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("ahoybrotherbear/MiniMax-M2.5-3bit-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 Settings
  • LM Studio
  • MLX LM

    How to use ahoybrotherbear/MiniMax-M2.5-3bit-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 "ahoybrotherbear/MiniMax-M2.5-3bit-MLX"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "ahoybrotherbear/MiniMax-M2.5-3bit-MLX"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "ahoybrotherbear/MiniMax-M2.5-3bit-MLX",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
MiniMax-M2.5-3bit-MLX
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  • 1 contributor
History: 3 commits
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ahoybrotherbear
Update README.md
5c4f648 verified 4 months ago
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  • README.md
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