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mlx-community
/
LLaDA2.1-mini-4bit

Image-Text-to-Text
MLX
Safetensors
llada2_moe
dllm
diffusion
llm
text_generation
conversational
custom_code
4-bit precision
Model card Files Files and versions
xet
Community

Instructions to use mlx-community/LLaDA2.1-mini-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use mlx-community/LLaDA2.1-mini-4bit with MLX:

    # Make sure mlx-vlm is installed
    # pip install --upgrade mlx-vlm
    
    from mlx_vlm import load, generate
    from mlx_vlm.prompt_utils import apply_chat_template
    from mlx_vlm.utils import load_config
    
    # Load the model
    model, processor = load("mlx-community/LLaDA2.1-mini-4bit")
    config = load_config("mlx-community/LLaDA2.1-mini-4bit")
    
    # Prepare input
    image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
    prompt = "Describe this image."
    
    # Apply chat template
    formatted_prompt = apply_chat_template(
        processor, config, prompt, num_images=1
    )
    
    # Generate output
    output = generate(model, processor, formatted_prompt, image)
    print(output)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
  • Pi

    How to use mlx-community/LLaDA2.1-mini-4bit 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/LLaDA2.1-mini-4bit"
    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/LLaDA2.1-mini-4bit"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use mlx-community/LLaDA2.1-mini-4bit 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/LLaDA2.1-mini-4bit"
    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/LLaDA2.1-mini-4bit
    Run Hermes
    hermes
LLaDA2.1-mini-4bit
9.17 GB
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  • 1 contributor
History: 2 commits
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prince-canuma
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  • .gitattributes
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  • README.md
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  • chat_template.jinja
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  • config.json
    1.85 kB
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  • configuration_llada2_moe.py
    3.16 kB
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  • model-00001-of-00002.safetensors
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    xet
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  • model-00002-of-00002.safetensors
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  • model.safetensors.index.json
    64.3 kB
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  • modeling_llada2_moe.py
    60.4 kB
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  • special_tokens_map.json
    180 Bytes
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  • tokenizer.json
    12.2 MB
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  • tokenizer_config.json
    489 Bytes
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