Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

skyuu72
/
Llama-Quantara-Sentinel-8B

Text Generation
Safetensors
GGUF
English
cybersecurity
security
defensive-security
vulnerability-detection
log-analysis
phishing-analysis
unsloth
qlora
conversational
Model card Files Files and versions
xet
Community

Instructions to use skyuu72/Llama-Quantara-Sentinel-8B 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 skyuu72/Llama-Quantara-Sentinel-8B 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 skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf skyuu72/Llama-Quantara-Sentinel-8B: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 skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf skyuu72/Llama-Quantara-Sentinel-8B: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 skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    Use Docker
    docker model run hf.co/skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use skyuu72/Llama-Quantara-Sentinel-8B with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "skyuu72/Llama-Quantara-Sentinel-8B"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "skyuu72/Llama-Quantara-Sentinel-8B",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
  • Ollama

    How to use skyuu72/Llama-Quantara-Sentinel-8B with Ollama:

    ollama run hf.co/skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use skyuu72/Llama-Quantara-Sentinel-8B with Docker Model Runner:

    docker model run hf.co/skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
  • Lemonade

    How to use skyuu72/Llama-Quantara-Sentinel-8B with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull skyuu72/Llama-Quantara-Sentinel-8B:Q4_K_M
    Run and chat with the model
    lemonade run user.Llama-Quantara-Sentinel-8B-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
Llama-Quantara-Sentinel-8B
13.8 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
skyuu72's picture
skyuu72
card: say the CTIBench TSVs aren't bundled and where to get them
1f48d18 verified 9 days ago
  • adapter
    v1.0 LoRA adapter - rebuild merged fp16 from this 13 days ago
  • evaluation
    harness.zip: add run_ctibench.py + the run_eval.py that actually has --no-system 9 days ago
  • .gitattributes
    1.74 kB
    v1.0 LoRA adapter - rebuild merged fp16 from this 13 days ago
  • ACCEPTABLE_USE.md
    7.17 kB
    v1.0 card, AUP, Modelfiles, evaluation evidence 13 days ago
  • Llama-Quantara-Sentinel-8B-v1.0.Q4_K_M.gguf
    4.92 GB
    xet
    v1.0 Q4_K_M 13 days ago
  • Llama-Quantara-Sentinel-8B-v1.0.Q8_0.gguf
    8.54 GB
    xet
    v1.0 Q8_0 13 days ago
  • Modelfile.Q4_K_M
    909 Bytes
    v1.0 card, AUP, Modelfiles, evaluation evidence 13 days ago
  • Modelfile.Q8_0
    905 Bytes
    v1.0 card, AUP, Modelfiles, evaluation evidence 13 days ago
  • NOTICE
    1.21 kB
    no-system-prompt safety verified: 46/46 refused, 0 leaks. + Meta attribution string 13 days ago
  • README-local-install.md
    2.63 kB
    v1.0 card, AUP, Modelfiles, evaluation evidence 13 days ago
  • README.md
    26.9 kB
    card: say the CTIBench TSVs aren't bundled and where to get them 9 days ago