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plutoedge
/
PlutoEdge-1.5B

GGUF
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iot
edge-ai
raspberry-pi
ollama
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Model card Files Files and versions
xet
Community

Instructions to use plutoedge/PlutoEdge-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use plutoedge/PlutoEdge-1.5B with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="plutoedge/PlutoEdge-1.5B",
    	filename="PlutoEdge-1.5B-v4-Q4_K_M.gguf",
    )
    
    llm.create_chat_completion(
    	messages = "No input example has been defined for this model task."
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use plutoedge/PlutoEdge-1.5B with llama.cpp:

    Install (macOS, Linux)
    curl -LsSf https://llama.app/install.sh | sh
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Use pre-built binary
    # Download pre-built binary from:
    # https://github.com/ggerganov/llama.cpp/releases
    # Start a local OpenAI-compatible server with a web UI:
    ./llama-server -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Build from source code
    git clone https://github.com/ggerganov/llama.cpp.git
    cd llama.cpp
    cmake -B build
    cmake --build build -j --target llama-server llama-cli
    # Start a local OpenAI-compatible server with a web UI:
    ./build/bin/llama-server -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Use Docker
    docker model run hf.co/plutoedge/PlutoEdge-1.5B:Q4_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use plutoedge/PlutoEdge-1.5B with Ollama:

    ollama run hf.co/plutoedge/PlutoEdge-1.5B:Q4_K_M
  • Unsloth Studio

    How to use plutoedge/PlutoEdge-1.5B with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for plutoedge/PlutoEdge-1.5B to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for plutoedge/PlutoEdge-1.5B to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for plutoedge/PlutoEdge-1.5B to start chatting
  • Pi

    How to use plutoedge/PlutoEdge-1.5B with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "plutoedge/PlutoEdge-1.5B:Q4_K_M"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use plutoedge/PlutoEdge-1.5B with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    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 plutoedge/PlutoEdge-1.5B:Q4_K_M
    Run Hermes
    hermes
  • Atomic Chat new
  • OpenClaw new

    How to use plutoedge/PlutoEdge-1.5B with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf plutoedge/PlutoEdge-1.5B:Q4_K_M
    Configure OpenClaw
    # Install OpenClaw:
    npm install -g openclaw@latest
    # Register the local server and set it as the default model:
    openclaw onboard --non-interactive --mode local \
      --auth-choice custom-api-key \
      --custom-base-url http://127.0.0.1:8080/v1 \
      --custom-model-id "plutoedge/PlutoEdge-1.5B:Q4_K_M" \
      --custom-provider-id llama-cpp \
      --custom-compatibility openai \
      --custom-text-input \
      --accept-risk \
      --skip-health
    Run OpenClaw
    openclaw agent --local --agent main --message "Hello from Hugging Face"
  • Docker Model Runner

    How to use plutoedge/PlutoEdge-1.5B with Docker Model Runner:

    docker model run hf.co/plutoedge/PlutoEdge-1.5B:Q4_K_M
  • Lemonade

    How to use plutoedge/PlutoEdge-1.5B with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull plutoedge/PlutoEdge-1.5B:Q4_K_M
    Run and chat with the model
    lemonade run user.PlutoEdge-1.5B-Q4_K_M
    List all available models
    lemonade list
PlutoEdge-1.5B
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  • 1 contributor
History: 8 commits
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    xet
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