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majentik
/
MiniMax-M2.7-TurboQuant-MLX-2bit

Text Generation
MLX
minimax
m2.7
Mixture of Experts
quantized
turboquant
kv-cache-quantization
Model card Files Files and versions
xet
Community

Instructions to use majentik/MiniMax-M2.7-TurboQuant-MLX-2bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use majentik/MiniMax-M2.7-TurboQuant-MLX-2bit with MLX:

    # Make sure mlx-lm is installed
    # pip install --upgrade mlx-lm
    # if on a CUDA device, also pip install mlx[cuda]
    
    # Generate text with mlx-lm
    from mlx_lm import load, generate
    
    model, tokenizer = load("majentik/MiniMax-M2.7-TurboQuant-MLX-2bit")
    
    prompt = "Once upon a time in"
    text = generate(model, tokenizer, prompt=prompt, verbose=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • LM Studio
  • MLX LM

    How to use majentik/MiniMax-M2.7-TurboQuant-MLX-2bit with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Generate some text
    mlx_lm.generate --model "majentik/MiniMax-M2.7-TurboQuant-MLX-2bit" --prompt "Once upon a time"
MiniMax-M2.7-TurboQuant-MLX-2bit
8.85 kB
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  • 1 contributor
History: 5 commits
majentik's picture
majentik
docs: upstream-first KV-cache guidance (q8_0/q4_0, mainline Hadamard rotation); fork demoted to experimental
cbc9315 verified about 11 hours ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    7.33 kB
    docs: upstream-first KV-cache guidance (q8_0/q4_0, mainline Hadamard rotation); fork demoted to experimental about 11 hours ago