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wolfCuanhamaRWS
/
GuardReasoner-3B_q5_k_m_gguf

Text Classification
Transformers
GGUF
English
llama-factory
full
Generated from Trainer
thesis_quant
q5_k_m_gguf
conversational
Model card Files Files and versions
xet
Community

Instructions to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf 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 wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    # Run inference directly in the terminal:
    llama cli -hf wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    # Run inference directly in the terminal:
    llama cli -hf wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_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 wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_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 wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    Use Docker
    docker model run hf.co/wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf with Ollama:

    ollama run hf.co/wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf with Docker Model Runner:

    docker model run hf.co/wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
  • Lemonade

    How to use wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull wolfCuanhamaRWS/GuardReasoner-3B_q5_k_m_gguf:Q5_K_M
    Run and chat with the model
    lemonade run user.GuardReasoner-3B_q5_k_m_gguf-Q5_K_M
    List all available models
    lemonade list
  • Atomic Chat
GuardReasoner-3B_q5_k_m_gguf
5.57 GB
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  • 1 contributor
History: 4 commits
wolfCuanhamaRWS's picture
wolfCuanhamaRWS
Upload folder using huggingface_hub
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  • .gitattributes
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  • README.md
    4.37 kB
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  • guardreasoner-3b.q5_k_m-00001-of-00001.gguf
    2.79 GB
    xet
    Upload folder using huggingface_hub over 1 year ago
  • guardreasoner-3b.q5_k_m.gguf
    2.79 GB
    xet
    Upload folder using huggingface_hub over 1 year ago