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mlx-community
/
gemma-4-e4b-it-4bit-MAD

Text Generation
MLX
Safetensors
English
gemma4
gemma
quantized
4bit-MAD
conversational
6-bit
Model card Files Files and versions
xet
Community

Instructions to use mlx-community/gemma-4-e4b-it-4bit-MAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use mlx-community/gemma-4-e4b-it-4bit-MAD 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("mlx-community/gemma-4-e4b-it-4bit-MAD")
    
    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 mlx-community/gemma-4-e4b-it-4bit-MAD with Pi:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "mlx-community/gemma-4-e4b-it-4bit-MAD"
    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": "mlx-community/gemma-4-e4b-it-4bit-MAD"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use mlx-community/gemma-4-e4b-it-4bit-MAD 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 "mlx-community/gemma-4-e4b-it-4bit-MAD"
    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 mlx-community/gemma-4-e4b-it-4bit-MAD
    Run Hermes
    hermes
  • MLX LM

    How to use mlx-community/gemma-4-e4b-it-4bit-MAD with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Interactive chat REPL
    mlx_lm.chat --model "mlx-community/gemma-4-e4b-it-4bit-MAD"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "mlx-community/gemma-4-e4b-it-4bit-MAD"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "mlx-community/gemma-4-e4b-it-4bit-MAD",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
gemma-4-e4b-it-4bit-MAD
4.23 GB
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  • 1 contributor
History: 3 commits
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N8Programs
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  • __pycache__
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  • .gitattributes
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  • README.md
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  • chat_template.jinja
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  • config.json
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  • dwq_padding_token_budget_metadata.json
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  • gemma4_mlx.py
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  • generation_config.json
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  • model.safetensors
    4.2 GB
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  • model.safetensors.index.json
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  • oldheldout_kl.log
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  • tokenizer.json
    32.2 MB
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  • tokenizer_config.json
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