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mardakani
/
Phi-3-mini-4k-instruct

GGUF
conversational
Model card Files Files and versions
xet
Community

Instructions to use mardakani/Phi-3-mini-4k-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use mardakani/Phi-3-mini-4k-instruct 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 mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf mardakani/Phi-3-mini-4k-instruct: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 mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf mardakani/Phi-3-mini-4k-instruct: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 mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    Use Docker
    docker model run hf.co/mardakani/Phi-3-mini-4k-instruct:Q4_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use mardakani/Phi-3-mini-4k-instruct with Ollama:

    ollama run hf.co/mardakani/Phi-3-mini-4k-instruct:Q4_K_M
  • Unsloth Studio

    How to use mardakani/Phi-3-mini-4k-instruct 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 mardakani/Phi-3-mini-4k-instruct 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 mardakani/Phi-3-mini-4k-instruct to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for mardakani/Phi-3-mini-4k-instruct to start chatting
  • Docker Model Runner

    How to use mardakani/Phi-3-mini-4k-instruct with Docker Model Runner:

    docker model run hf.co/mardakani/Phi-3-mini-4k-instruct:Q4_K_M
  • Lemonade

    How to use mardakani/Phi-3-mini-4k-instruct with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull mardakani/Phi-3-mini-4k-instruct:Q4_K_M
    Run and chat with the model
    lemonade run user.Phi-3-mini-4k-instruct-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
Phi-3-mini-4k-instruct
15.5 GB
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  • 1 contributor
History: 12 commits
mardakani's picture
mardakani
Update performance.sh
61709e8 verified about 2 years ago
  • .gitattributes
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    Upload phi-3.gguf about 2 years ago
  • performance.sh
    814 Bytes
    Update performance.sh about 2 years ago
  • phi-3-Q2_k.gguf
    1.42 GB
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  • phi-3-Q4_K_M.gguf
    2.39 GB
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  • phi-3-Q8_0.gguf
    4.06 GB
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  • phi-3.gguf
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